Farmers today face a number of challenges, from supply chain stability to nutrient and waste management. But hanging over everything is the need to maintain profitability amid changing markets and increased uncertainty.

Fyto, founded by former MIT staff member Jason Prapas, is offering a highly automated cultivation system to address several of farmers’ biggest problems at once.

At the heart of Fyto’s system is Lemna, a genus of small aquatic plants otherwise known as duckweed. Most people have probably seen thick green mats of Lemna lying on top of ponds and swamps. But Lemna is also rich in protein and capable of doubling in biomass every two days. Fyto has built an automated cropping system that uses nitrogen-rich wastewater from dairy farms to grow Lemna in shallow pools on otherwise less productive farmland. On top of the pools, the company has built what it believes are the largest agricultural robots in the world, which monitor plant health and harvest the Lemna sustainably. The Lemna can then be used on farms as a high-protein cattle feed or fertilizer supplement.

Fyto’s systems are designed to rely on minimal land, water, and labor while creating a more sustainable, profitable food system.

“We developed from scratch a robotic system that takes the guesswork out of farming this crop,” says Prapas, who previously led the translational research program of MIT’s Tata Center. “It looks at the crop on a daily basis, takes inventory to know how many plants there are, how much should be harvested to have healthy growth the next day, can detect if the color is slightly off or there are nutrient deficiencies, and can suggest different interventions based on all that data.”

From kiddie pools to cow farms

Prapas’ first job out of college was with an MIT spinout called Green Fuel that harvested algae to make biofuel. He went back to school for a master’s and then a PhD in mechanical engineering, but he continued working with startups. Following his PhD at Colorado State University, he co-founded Factor[e] Ventures to fund and incubate startups focused on improving energy access in emerging markets.

Through that work, Prapas was introduced to MIT’s Tata Center for Technology and Design.

“We were really interested in the new technologies being developed at the MIT Tata Center, and in funding new startups taking on some of these global climate challenges in emerging markets,” Prapas recalls. “The Tata Center was interested in making sure these technologies get put into practice rather than patented and put on a shelf somewhere. It was a good synergy.”

One of the people Prapas got to know was Rob Stoner, the founding director of the Tata Center, who encouraged Prapas to get more directly involved with commercializing new technologies. In 2017, Prapas joined the Tata Center as the translational research director. During that time, Prapas worked with MIT students, faculty, and staff to test their inventions in the real world. Much of that work involved innovations in agriculture.

“Farming is a fact of life for a lot of folks around the world — both subsistence farming but also producing food for the community and beyond,” Prapas says. “That has huge implications for water usage, electricity consumption, labor. For years, I’d been thinking about how we make farming a more attractive endeavor for people: How do we make it less back-breaking, more efficient, and more economical?”

Between his work at MIT and Factor[e], Prapas visited hundreds of farms around the world, where he started to think about the lack of good choices for farming inputs like animal feed and fertilizers. The problem represented a business opportunity.

Fyto began with kiddie pools. Prapas started growing aquatic plants in his backyard, using them as a fertilizer source for vegetables. The experience taught him how difficult it would be to train people to grow and harvest Lemna at large scales on farms.

“I realized we’d have to invent both the farming method — the agronomy — and the equipment and processes to grow it at scale cost effectively,” Prapas explains.

Prapas started discussing his ideas with others around 2019.

“The MIT and Boston ecosystems are great for pitching somewhat crazy ideas to willing audiences and seeing what sticks,” Prapas says. “There’s an intangible benefit of being at MIT, where you just can’t help but think of bold ideas and try putting them into practice.”

Prapas, who left MIT to lead Fyto in 2019, partnered with Valerie Peng ’17, SM ’19, then a graduate student at MIT who became his first hire.

“Farmers work so hard, and I have so much respect for what they do,” says Peng, who serves as Fyto’s head of engineering. “People talk about the political divide, but there’s a lot of alignment around using less, doing more with what you have, and making our food systems more resilient to drought, supply chain disruptions, and everything else. There’s more in common with everyone than you’d expect.”

A new farming method

Lemna can produce much more protein per acre than soy, another common source of protein on farms, but it requires a lot of nitrogen to grow. Fortunately, many types of farmers, especially large dairy farmers, have abundant nitrogen sources in the waste streams that come from washing out cow manure.

“These waste streams are a big problem: In California it’s believed to be one of the largest source of greenhouse gas emissions in the agriculture sector despite the fact that hundreds of crops are grown in California,” Prapas says.

For the last few years, Fyto has run its systems in pilots on farms, trialing the crop as feed and fertilizer before delivering to its customers. The systems Fyto has deployed so far are about 50 feet wide, but it is actively commissioning its newest version that’s 160 feet wide. Eventually, Fyto plans to sell the systems directly to farmers.

Fyto is currently awaiting California’s approval for use in feed, but Lemna has already been approved in Europe. Fyto has also been granted a fertilizer license on its plant-based fertilizer, with promising early results in trials, and plans to sell new fertilizer products this year.

Although Fyto is focused on dairy farms for its early deployments, it has also grown Lemna using manure from chicken, and Prapas notes that even people like cheese producers have a nitrogen waste problem that Fyto could solve.

“Think of us like a polishing step you could put on the end of any system that has an organic waste stream,” Prapas says. “In that situation, we’re interested in growing our crops on it. We’ve had very few things that the plant can’t grow on. Globally, we see this as a new farming method, and that means it’s got a lot of potential applications.”

What if data could help predict a patient’s prognosis, streamline hospital operations, or optimize human resources in medicine? A book fresh off the shelves, “The Analytics Edge in Healthcare,” shows that this is already happening, and demonstrates how to scale it. 

Authored by Dimitris Bertsimas, MIT’s vice provost for open learning, along with two of Bertsimas’ former students — Agni Orfanoudaki PhD ’21, associate professor of operations management at University of Oxford’s Saïd Business School, and Holly Wiberg PhD ’22, assistant professor of public policy and operations research at Carnegie Mellon University — the book provides a practical introduction to the field of health care analytics. With an emphasis on real-world applications, the first part of the book establishes technical foundations — spanning machine learning and optimization — while the second part of the book presents integrated case studies that cover various clinical specialties and problem types using descriptive, predictive, and prescriptive analytics. 

Part of a broader series, “The Analytics Edge in Healthcare” demonstrates how to leverage data and models to make better decisions within the health care sector, while its predecessor, “The Analytics Edge,” dives into the science of using data to build models, improve decisions, and add value to institutions and individuals. 

Bertsimas, who is also the associate dean of business analytics and the Boeing Leaders for Global Operations Professor of Management at the MIT Sloan School of Management, is the innovator behind 15.071 (The Analytics Edge), a course on MIT Open Learning’s MITx that has attracted hundreds of thousands of online learners and served as the inspiration behind the book series. Bertsimas took a break from research and his work at MIT Open Learning to discuss how the field of analytics is transforming the health care system and share some surprising ways analytics are already being used in hospitals. 

Q: How is the field of analytics changing the way hospitals provide care and manage their operations?

A: As an academic, I’ve always aspired to educate, write publications, and utilize what we do in practice. Therefore, I founded Holistic Hospital Optimization (H20) with the goal of optimizing hospital operations with machine learning to improve patient care. We have developed a variety of tools at MIT and implemented them at hospitals around the world. For example, we manage patients’ length of stay and their deterioration indexes (a computerized tool that predicts a patient’s risk of clinical deterioration); we manage nurse optimization and how hospitals can allocate human resources appropriately; and we optimize blocks for surgeries. This is the beginning of a change where analytics and AI methods are now being utilized quite widely. My hope would be that this work and this book will accelerate the effect of using these tools. 

Additionally, I have taught a nine-lecture course twice with Agni and Holly at the Hartford Hospital System, where I realized that these analytics methods — which are typically not taught in medical schools — can be demonstrated for health care practitioners, including physicians, nurses, and administrators. To have an impact, you need to have appropriate methods, implement them, and apply them, but you also need to educate people on how to use them. This links well with my role at Open Learning, where our objective is to educate learners globally. In fact, Open Learning is launching this fall Universal AI, a dynamic online learning experience that provides comprehensive knowledge on artificial intelligence, preparing a global audience of learners for employment in our rapidly evolving job market. 

Q: What are some surprising ways analytics are being used in health care that most people wouldn’t expect?

A: Using analytics, we have reduced patients’ length of stay at Hartford Hospital from 5.67 days to five days. We have an algorithm that predicts patients’ probability of being released; therefore, doctors prioritize the patients with the highest probability, preparing them for discharge. This means that the hospital can treat far more patients, and the patients stay in the hospital less time.

Furthermore, when hospitals saw an increase in nurse turnover during the Covid-19 pandemic, we developed an analytics system that takes into account equity and fairness and decreases overtime costs, giving preferred slots to nurses and decreasing overall turnover substantially. These are just two examples; there are many others where an analytical perspective to health care and medicine has made a material difference. 

Q: Looking ahead, how do you see artificial intelligence shaping the future of health care?

A: In a very significant way — we use machine learning to make better predictions, but generative AI can explain them. I already see a movement in that direction. It’s really the evolution of AI that made this possible, and it is exciting. It’s also important for the world, because of its capabilities to improve care and save lives. 

For example, through our program at the Hartford Hospital System, we discovered that a patient was getting worse and predicted through analytics that they would get even worse. After our prediction, the doctors examined the patient more closely and discovered the patient had an early case of sepsis, a life-threatening condition in which the body responds improperly to an infection. If we hadn’t detected sepsis earlier, the patient might have died. This made an actual difference in saving a person’s life. 

Q: If you had to describe “The Analytics Edge in Healthcare” in one or two words, what would they be, and why? 

A: The book is a phased transition in health care because it is capable of affecting the health care sector in a way that has not been done before. The book really outlines my work in health care and its applications in the last decade.

If there’s one thing that characterizes driving in any major city, it’s the constant stop-and-go as traffic lights change and as cars and trucks merge and separate and turn and park. This constant stopping and starting is extremely inefficient, driving up the amount of pollution, including greenhouse gases, that gets emitted per mile of driving. 

One approach to counter this is known as eco-driving, which can be installed as a control system in autonomous vehicles to improve their efficiency.

How much of a difference could that make? Would the impact of such systems in reducing emissions be worth the investment in the technology? Addressing such questions is one of a broad category of optimization problems that have been difficult for researchers to address, and it has been difficult to test the solutions they come up with. These are problems that involve many different agents, such as the many different kinds of vehicles in a city, and different factors that influence their emissions, including speed, weather, road conditions, and traffic light timing.

“We got interested a few years ago in the question: Is there something that automated vehicles could do here in terms of mitigating emissions?” says Cathy Wu, the Thomas D. and Virginia W. Cabot Career Development Associate Professor in the Department of Civil and Environmental Engineering and the Institute for Data, Systems, and Society (IDSS) at MIT, and a principal investigator in the Laboratory for Information and Decision Systems. “Is it a drop in the bucket, or is it something to think about?,” she wondered.

To address such a question involving so many components, the first requirement is to gather all available data about the system, from many sources. One is the layout of the network’s topology, Wu says, in this case a map of all the intersections in each city. Then there are U.S. Geological Survey data showing the elevations, to determine the grade of the roads. There are also data on temperature and humidity, data on the mix of vehicle types and ages, and on the mix of fuel types.

Eco-driving involves making small adjustments to minimize unnecessary fuel consumption. For example, as cars approach a traffic light that has turned red, “there’s no point in me driving as fast as possible to the red light,” she says. By just coasting, “I am not burning gas or electricity in the meantime.” If one car, such as an automated vehicle, slows down at the approach to an intersection, then the conventional, non-automated cars behind it will also be forced to slow down, so the impact of such efficient driving can extend far beyond just the car that is doing it.

That’s the basic idea behind eco-driving, Wu says. But to figure out the impact of such measures, “these are challenging optimization problems” involving many different factors and parameters, “so there is a wave of interest right now in how to solve hard control problems using AI.” 

The new benchmark system that Wu and her collaborators developed based on urban eco-driving, which they call “IntersectionZoo,” is intended to help address part of that need. The benchmark was described in detail in a paper presented at the 2025 International Conference on Learning Representation in Singapore.

Looking at approaches that have been used to address such complex problems, Wu says an important category of methods is multi-agent deep reinforcement learning (DRL), but a lack of adequate standard benchmarks to evaluate the results of such methods has hampered progress in the field.

The new benchmark is intended to address an important issue that Wu and her team identified two years ago, which is that with most existing deep reinforcement learning algorithms, when trained for one specific situation (e.g., one particular intersection), the result does not remain relevant when even small modifications are made, such as adding a bike lane or changing the timing of a traffic light, even when they are allowed to train for the modified scenario.

In fact, Wu points out, this problem of non-generalizability “is not unique to traffic,” she says. “It goes back down all the way to canonical tasks that the community uses to evaluate progress in algorithm design.” But because most such canonical tasks do not involve making modifications, “it’s hard to know if your algorithm is making progress on this kind of robustness issue, if we don’t evaluate for that.”

While there are many benchmarks that are currently used to evaluate algorithmic progress in DRL, she says, “this eco-driving problem features a rich set of characteristics that are important in solving real-world problems, especially from the generalizability point of view, and that no other benchmark satisfies.” This is why the 1 million data-driven traffic scenarios in IntersectionZoo uniquely position it to advance the progress in DRL generalizability.  As a result, “this benchmark adds to the richness of ways to evaluate deep RL algorithms and progress.”

And as for the initial question about city traffic, one focus of ongoing work will be applying this newly developed benchmarking tool to address the particular case of how much impact on emissions would come from implementing eco-driving in automated vehicles in a city, depending on what percentage of such vehicles are actually deployed.

But Wu adds that “rather than making something that can deploy eco-driving at a city scale, the main goal of this study is to support the development of general-purpose deep reinforcement learning algorithms, that can be applied to this application, but also to all these other applications — autonomous driving, video games, security problems, robotics problems, warehousing, classical control problems.”

Wu adds that “the project’s goal is to provide this as a tool for researchers, that’s openly available.” IntersectionZoo, and the documentation on how to use it, are freely available at GitHub.

Wu is joined on the paper by lead authors Vindula Jayawardana, a graduate student in MIT’s Department of Electrical Engineering and Computer Science (EECS); Baptiste Freydt, a graduate student from ETH Zurich; and co-authors Ao Qu, a graduate student in transportation; Cameron Hickert, an IDSS graduate student; and Zhongxia Yan PhD ’24. 

Tuberculosis, the world’s deadliest infectious disease, is estimated to infect around 10 million people each year, and kills more than 1 million annually. Once established in the lungs, the bacteria’s thick cell wall helps it to fight off the host immune system.

Much of that cell wall is made from complex sugar molecules known as glycans, but it’s not well-understood how those glycans help to defend the bacteria. One reason for that is that there hasn’t been an easy way to label them inside cells.

MIT chemists have now overcome that obstacle, demonstrating that they can label a glycan called ManLAM using an organic molecule that reacts with specific sulfur-containing sugars. These sugars are found in only three bacterial species, the most notorious and prevalent of which is Mycobacterium tuberculosis, the microbe that causes TB.

After labeling the glycan, the researchers were able to visualize where it is located within the bacterial cell wall, and to study what happens to it throughout the first few days of tuberculosis infection of host immune cells.

The researchers now hope to use this approach to develop a diagnostic that could detect TB-associated glycans, either in culture or in a urine sample, which could offer a cheaper and faster alternative to existing diagnostics. Chest X-rays and molecular diagnostics are very accurate but are not always available in developing nations where TB rates are high. In those countries, TB is often diagnosed by culturing microbes from a sputum sample, but that test has a high false negative rate, and it can be difficult for some patients, especially children, to provide a sputum sample. This test also requires many weeks for the bacteria to grow, delaying diagnosis.

“There aren’t a lot of good diagnostic options, and there are some patient populations, including children, who have a hard time giving samples that can be analyzed. There’s a lot of impetus to develop very simple, fast tests,” says Laura Kiessling, the Novartis Professor of Chemistry at MIT and the senior author of the study.

MIT graduate student Stephanie Smelyansky is the lead author of the paper, which appears this week in the Proceedings of the National Academy of Sciences. Other authors include Chi-Wang Ma, an MIT postdoc; Victoria Marando PhD ’23; Gregory Babunovic, a postdoc at the Harvard T.H. Chan School of Public Health; So Young Lee, an MIT graduate student; and Bryan Bryson, an associate professor of biological engineering at MIT.

Labeling glycans

Glycans are found on the surfaces of most cells, where they perform critical functions such as mediating communication between cells.In bacteria, glycans help the microbes to enter host cells, and they also appear to communicate with the host immune system, in some cases blocking the immune response.

“Mycobacterium tuberculosis has a really elaborate cell envelope compared to other bacteria, and it’s a rich structure that’s composed of a lot of different glycans,” Smelyansky says. “Something that’s often underappreciated is the fact that these glycans can also interact with our host cells. When our immune cells recognize these glycans, instead of sending out a danger signal, it can send the opposite message, that there’s no danger.”

Glycans are notoriously difficult to tag with any kind of probe, because unlike proteins or DNA, they don’t have distinctive sequences or chemical reactivities that can be targeted. And unlike proteins, they are not genetically encoded, so cells can’t be genetically engineered to produce sugars labeled with fluorescent tags such as green fluorescent protein.

One of the key glycans in M. tuberculosis, known as ManLAM, contains a rare sugar known as MTX, which is unusual in that it has a thioether — a sulfur atom sandwiched between two carbon atoms. This chemical group presented an opportunity to use a small-molecule tag that had been previously developed for labeling methionine, an  amino acid that contains a similar group.

The researchers showed that they could use this tag, known as an oxaziridine, to label ManLAM in M. tuberculosis. The researchers linked the oxaziridine to a fluorescent probe and showed that in M. tuberculosis, this tag showed up in the outer layer of the cell wall. When the researchers exposed the label to Mycobacterium smegmatis, a related bacterium that does not cause disease and does not have the sugar MTX, they saw no fluorescent signal.

“This is the first approach that really selectively allows us to visualize one glycan in particular,” Smelyansky says.

Better diagnostics

The researchers also showed that after labeling ManLAM in M. tuberculosis cells, they could track the cells as they infected immune cells called macrophages. Some tuberculosis researchers had hypothesized that the bacterial cells shed ManLAM once inside a host cell, and that those free glycans then interact with the host immune system. However, the MIT team found that the glycan appears to remain in the bacterial cell walls for at least the first few days of infection.

“The bacteria still have their cell walls attached to them. So it may be that some glycan is being released, but the majority of it is retained on the bacterial cell surface, which has never been shown before,” Smelyansky says.

The researchers now plan to use this approach to study what happens to the bacteria following treatment with different antibiotics, or immune stimulation of the macrophages. It could also be used to study in more detail how the bacterial cell wall is assembled, and how ManLAM helps bacteria get into macrophages and other cells.

“Having a handle to follow the bacteria is really valuable, and it will allow you to visualize processes, both in cells and in animal models, that were previously invisible,” Kiessling says.

She also hopes to use this approach to create new diagnostics for tuberculosis. There is currently a diagnostic in development that uses antibodies to detect ManLAM in a urine sample. However, this test only works well in patients with very active cases of TB, especially people who are immunosuppressed because of HIV or other conditions.

Using their small-molecule sensor instead of antibodies, the MIT team hopes to develop a more sensitive test that could detect ManLAM in the urine even when only small quantities are present.

“This is a beautifully elegant approach to selectively label the surface of mycobacteria, enabling real-time monitoring of cell wall dynamics in this important bacterial family. Such investigations will inform the development of novel strategies to diagnose, prevent, and treat mycobacterial disease, most notably tuberculosis, which remains a global health challenge,” says Todd Lowary, a distinguished research fellow at the Institute of Biological Chemistry, Academia Sinica, Taipei Taiwan, who was not involved in the research.

The research was funded by the National Institute of Allergy and Infectious Disease, the National Institutes of Health, the National Science Foundation, and the Croucher Fellowship.

MIT physicists have captured the first images of individual atoms freely interacting in space. The pictures reveal correlations among the “free-range” particles that until now were predicted but never directly observed. Their findings, appearing today in the journal Physical Review Letters, will help scientists visualize never-before-seen quantum phenomena in real space.

The images were taken using a technique developed by the team that first allows a cloud of atoms to move and interact freely. The researchers then turn on a lattice of light that briefly freezes the atoms in their tracks, and apply finely tuned lasers to quickly illuminate the suspended atoms, creating a picture of their positions before the atoms naturally dissipate.

The physicists applied the technique to visualize clouds of different types of atoms, and snapped a number of imaging firsts. The researchers directly observed atoms known as “bosons,” which bunched up in a quantum phenomenon to form a wave. They also captured atoms known as “fermions” in the act of pairing up in free space — a key mechanism that enables superconductivity.

“We are able to see single atoms in these interesting clouds of atoms and what they are doing in relation to each other, which is beautiful,” says Martin Zwierlein, the Thomas A. Frank Professor of Physics at MIT.

In the same journal issue, two other groups report using similar imaging techniques, including a team led by Nobel laureate Wolfgang Ketterle, the John D. MacArthur Professor of Physics at MIT. Ketterle’s group visualized enhanced pair correlations among bosons, while the other group, from École Normale Supérieure in Paris, led by Tarik Yefsah, a former postdoc in Zwierlein’s lab, imaged a cloud of noninteracting fermions.

The study by Zwierlein and his colleagues is co-authored by MIT graduate students Ruixiao Yao, Sungjae Chi, and Mingxuan Wang, and MIT assistant professor of physics Richard Fletcher.

Inside the cloud

A single atom is about one-tenth of a nanometer in diameter, which is one-millionth of the thickness of a strand of human hair. Unlike hair, atoms behave and interact according to the rules of quantum mechanics; it is their quantum nature that makes atoms difficult to understand. For example, we cannot simultaneously know precisely where an atom is and how fast it is moving.

Scientists can apply various methods to image individual atoms, including absorption imaging, where laser light shines onto the atom cloud and casts its shadow onto a camera screen.

“These techniques allow you to see the overall shape and structure of a cloud of atoms, but not the individual atoms themselves,” Zwierlein notes. “It’s like seeing a cloud in the sky, but not the individual water molecules that make up the cloud.”

He and his colleagues took a very different approach in order to directly image atoms interacting in free space. Their technique, called “atom-resolved microscopy,” involves first corralling a cloud of atoms in a loose trap formed by a laser beam. This trap contains the atoms in one place where they can freely interact. The researchers then flash on a lattice of light, which freezes the atoms in their positions. Then, a second laser illuminates the suspended atoms, whose fluorescence reveals their individual positions.

“The hardest part was to gather the light from the atoms without boiling them out of the optical lattice,” Zwierlein says. “You can imagine if you took a flamethrower to these atoms, they would not like that. So, we’ve learned some tricks through the years on how to do this. And it’s the first time we do it in-situ, where we can suddenly freeze the motion of the atoms when they’re strongly interacting, and see them, one after the other. That’s what makes this technique more powerful than what was done before.”

Bunches and pairs

The team applied the imaging technique to directly observe interactions among both bosons and fermions. Photons are an example of a boson, while electrons are a type of fermion. Atoms can be bosons or fermions, depending on their total spin, which is determined by whether the total number of their protons, neutrons, and electrons is even or odd. In general, bosons attract, whereas fermions repel.

Zwierlein and his colleagues first imaged a cloud of bosons made up of sodium atoms. At low temperatures, a cloud of bosons forms what’s known as a Bose-Einstein condensate — a state of matter where all bosons share one and the same quantum state. MIT’s Ketterle was one of the first to produce a Bose-Einstein condensate, of sodium atoms, for which he shared the 2001 Nobel Prize in Physics.

Zwierlein’s group now is able to image the individual sodium atoms within the cloud, to observe their quantum interactions. It has long been predicted that bosons should “bunch” together, having an increased probability to be near each other. This bunching is a direct consequence of their ability to share one and the same quantum mechanical wave. This wave-like character was first predicted by physicist Louis de Broglie. It is the “de Broglie wave” hypothesis that in part sparked the beginning of modern quantum mechanics.

“We understand so much more about the world from this wave-like nature,” Zwierlein says. “But it’s really tough to observe these quantum, wave-like effects. However, in our new microscope, we can visualize this wave directly.”

In their imaging experiments, the MIT team were able to see, for the first time in situ, bosons bunch together as they shared one quantum, correlated de Broglie wave. The team also imaged a cloud of two types of lithium atoms. Each type of atom is a fermion, that naturally repels its own kind, but that can strongly interact with other particular fermion types. As they imaged the cloud, the researchers observed that indeed, the opposite fermion types did interact, and formed fermion pairs — a coupling that they could directly see for the first time.

“This kind of pairing is the basis of a mathematical construction people came up with to explain experiments. But when you see pictures like these, it’s showing in a photograph, an object that was discovered in the mathematical world,” says study co-author Richard Fletcher. “So it’s a very nice reminder that physics is about physical things. It’s real.”

Going forward, the team will apply their imaging technique to visualize more exotic and less understood phenomena, such as “quantum Hall physics” — situations when interacting electrons display novel correlated behaviors in the presence of a magnetic field.

“That’s where theory gets really hairy — where people start drawing pictures instead of being able to write down a full-fledged theory because they can’t fully solve it,” Zwierlein says. “Now we can verify whether these cartoons of quantum Hall states are actually real. Because they are pretty bizarre states.”

This work was supported, in part, by National Science Foundation through the MIT-Harvard Center for Ultracold Atoms, as well as by the Air Force Office of Scientific Research, the Army Research Office, the Department of Energy, the Defense Advanced Projects Research Agency, a Vannevar Bush Faculty Fellowship, and the David and Lucile Packard Foundation.

Caring well for the elderly is a familiar challenge. Some elderly people need close medical attention in facilities; others struggle with reduced capabilities while not wanting to leave their homes. For families, finding good care is hard and expensive, and already-burdened family members often pick up the slack.

The problem is expanding as birthrates drop while some segments of the population live longer, meaning that a growing portion of the population is elderly. In the U.S., there are currently three states currently where at least 20 percent of the population is 65 and older. (Yes, Florida is one.) But by 2050, demographic trends suggest, there will be 43 states with that profile.

In age terms, “America is becoming Florida,” quips MIT economist Jonathan Gruber. “And it’s not just America. The whole world is aging rapidly. The share of the population over 65 is growing rapidly everywhere, and within that, the share of the elderly that are over 85 is growing rapidly.”

In a new edited volume, Gruber and several other scholars explore the subject from a global perspective. The book, “Long-Term Care around the World,” is published this month by the University of Chicago Press. The co-editors are Gruber, the Ford Professor of Economics and chair of the Department of Economics at MIT; and Kathleen McGarry, a professor of economics at Stony Brook University.

The book looks at 10 relatively wealthy countries and how they approach the problem of long-term care. In their chapter about the U.S., Gruber and McGarry emphasize a remarkable fact: About one-third of long-term care for the elderly in the U.S. is informal, provided by family and friends, despite limited time and resources. Overall, long-term care is 2 percent of U.S. GDP.

“We have two fundamental long-term care problems in the U.S.,” Gruber says. “Too much informal care at home, and, relatedly, not enough options for elders to live with effective care in ‘congregate housing’ [or elder communities], even if they’re not sick enough for a nursing facility.”

The nature of the problem

The needs of the elderly sit in plain sight. In the U.S., about 30 percent of people 65 and over, and 60 percent of people 85 and over report limitations in basic activities. Getting dressed and taking baths are among the most common daily problems; shopping for groceries and managing money are also widely reported issues. Additionally, these limitations have mental health implications. About 10 percent of the elderly report depression, rising to 30 percent among those who struggle with three or more types of basic daily tasks.

Even so, the U.S. is not actually heavily dotted with nursing homes. In a country of about 330 million people, with 62 million being 65 and over, it’s unusual for an elderly person to be in one.

“We all think of nursing homes as where you go when you’re old, but there are only about 1.2 million people in nursing homes in America,” Gruber observes. “Which is a lot, but tiny compared to the share of people who are elderly in the U.S. and who have needs. Most people who have needs get them met at home.”

And while nursing homes can be costly, home care is too. Given an average U.S. salary of $23 per hour for a home health care aide, annual costs can reach six figures even with half-time care. As a result, many families simply help their elderly relatives as best they can.

Therefore, Gruber has found, we must account for the informal costs of elder care, too. Ultimately, Gruber says, informal help represents “an inefficient system of people taking care of their elderly parents at home, which is a stress on the family, and the elders don’t get enough care.”

To be sure, some people buy private long-term care insurance to defray these costs. But this is a tricky market, where insurers are concerned about “adverse selection,” people buying policies with a distinct need for them (beyond what insurers can detect). Rates therefore can seem high, and for limited, conditional benefits. Research by MIT economist Amy Finkelstein has shown that only 18 percent of long-term insurance policies are used.

“Private long-term care insurance is a market that just hasn’t worked well,” Gruber says. “It’s basically a fixed amount of money, should you meet certain conditions. And people are surprised by that, and it doesn’t meet their needs, and it’s expensive. We need a public solution.”

Congregate housing, a possible solution

Looking at long-term care internationally helps identify what those solutions might be. The U.S. does not neglect elder care, but could clearly broaden its affordable options.

“On the one hand, what jumped out at me is how normal the U.S. is,” Gruber says. “We’re in the middle of the pack in terms of the share of GDP we spend on long-term care.” However, some European countries that spend a similar share and also rely heavily on informal elder care, including Italy and Spain, have notably lower levels of GDP per capita.

Some other European countries with income levels closer to the U.S., including Germany and the Netherlands, do spend more on long-term elder care. The Netherlands tops the list by devoting about 4 percent of its GDP to this area.

However, in the U.S., the issue is not so much drastically changing how much it spends on long-term elder care, but how it spends. The Dutch have a relatively more extensive system of elder communities — the “congregate housing” for the elderly who are not desperately unwell, but simply find self-reliance increasingly hard.

“That’s the huge missing hole in the U.S. long-term care system, what do we do with people who aren’t sick enough for a nursing home, but probably shouldn’t be at home,” Gruber says. “Right now they stay at home, they’re lonely, they’re not getting services, their kids are super-stressed out, and they’re pulling millions of people out of the labor force, especially women. Everyone is unhappy about it, and they’re not growing GDP, so it’s hurting our economy and our well-being.”

Overall, then, Gruber thinks further investment in elder-care communities would be an example of effective government spending that can address the brewing crisis in long-term care — although it would require new federal legislation in a highly polarized political environment.

Could that happen? Could the U.S. invest more now and realize long-term financial benefits, while allowing working-age employees to spend more time at their jobs rather than acting as home caregivers? Making people more aware of the issue, Gruber thinks, is a necessary starting point.

“If anything might be bipartisan, it could be long-term care,” Gruber says. “Everybody has parents. A solution has to be bipartisan. Long-term care may be one of those areas where it’s possible.”

Support for the research was provided, in part, by the National Institute on Aging.

A team from MIT Lincoln Laboratory has built and demonstrated the wideband selective propagation radar (WiSPR), a system capable of seeing out various distances at millimeter-wave (mmWave or MMW) frequencies. Typically, these high frequencies, which range from 30 to 300 gigahertz (GHz), are employed for only short-range operations. Using transmit-and-receive electronically scanned arrays of many antenna elements each, WiSPR produces narrow beams capable of quickly scanning around an area to detect objects of interest. The narrow beams can also be manipulated into broader beams for communications.

"Building a system with sufficient sensitivity to operate over long distances at these frequencies for radar and communications functions is challenging," says Greg Lyons, a senior staff member in the Airborne Radar Systems and Techniques Group, part of Lincoln Laboratory's ISR Systems and Technology R&D area. "We have many radar experts in our group, and we all debated whether such a system was even feasible. Much innovation is happening in the commercial sector, and we leveraged those advances to develop this multifunctional system."

The high signal bandwidth available at mmWave makes these frequencies appealing. Available licensed frequencies are quickly becoming overloaded, and harnessing mmWave frequencies frees up considerable bandwidth and reduces interference between systems. A high signal bandwidth is useful in a communications system to transmit more information, and in a radar system to improve range resolution (i.e., ability of radar to distinguish between objects in the same angular direction but at different distances from the radar).

The phases for success

In 2019, the laboratory team set out to assess the feasibility of their mmWave radar concept. Using commercial off-the-shelf radio-frequency integrated circuits (RFICs), which are chips that send and receive radio waves, they built a fixed-beam system (only capable of staring in one direction, not scanning) with horn antennas. During a demonstration on a foggy day at Joint Base Cape Cod, the proof-of-concept system successfully detected calibration objects at unprecedented ranges.  

"How do you build a prototype for what will eventually be a very complicated system?" asks program manager Christopher Serino, an assistant leader of the Airborne Radar Systems and Techniques Group. "From this feasibility testing, we showed that such a system could actually work, and identified the technology challenges. We knew those challenges would require innovative solutions, so that's where we focused our initial efforts."

WiSPR is based on multiple-element antenna arrays. Whether serving a radar or communications function, the arrays are phased, which means the phase between each antenna element is adjusted. This adjustment ensures all phases add together to steer the narrow beams in the desired direction. With this configuration of multiple elements phased up, the antenna becomes more directive in sending and receiving energy toward one location. (Such phased arrays are becoming ubiquitous in technologies like 5G smartphones, base stations, and satellites.)

To enable the tiny beams to continuously scan for objects, the team custom-built RFICs using state-of-the-art semiconductor technology and added digital capabilities to the chips. By controlling the behavior of these chips with custom firmware and software, the system can search for an object and, after the object is found, keep it in "track" while the search for additional objects continues — all without physically moving antennas or relying on an operator to tell the system what to do next.

"Phasing up elements in an array to get gain in a particular direction is standard practice," explains Deputy Program Manager David Conway, a senior staff member in the Integrated RF and Photonics Group. "What isn't standard is having this many elements with the RF at millimeter wavelengths still working together, still summing up their energy in transmit and receive, and capable of quickly scanning over very wide angles."

Line 'em up and cool 'em down

For the communications function, the team devised a novel beam alignment procedure.

"To be able to combine many antenna elements to have a radar reach out beyond typical MMW operating ranges — that's new," Serino says. "To be able to electronically scan the beams around as a radar with effectively zero latency between beams at these frequencies — that's new. Broadening some of those beams so you're not constantly reacquiring and repointing during communications — that's also new."

Another innovation key to WiSPR's development is a cooling arrangement that removes the large amount of heat dissipated in a small area behind the transmit elements, each having their own power amplifier.

Last year, the team demonstrated their prototype WiSPR system at the U.S. Army Aberdeen Proving Ground in Maryland, in collaboration with the U.S. Army Rapid Capabilities and Critical Technologies Office and the U.S. Army Test and Evaluation Command. WiSPR technology has since been transitioned to a vendor for production. By adopting WiSPR, Army units will be able to conduct their missions more effectively.

"We're anticipating that this system will be used in the not-too-distant future," Lyons says. "Our work has pushed the state of the art in MMW radars and communication systems for both military and commercial applications."

"This is exactly the kind of work Lincoln Laboratory is proud of: keeping an eye on the commercial sector and leveraging billions-of-dollars investments to build new technology, rather than starting from scratch," says Lincoln Laboratory assistant director Marc Viera.

This effort supported the U.S. Army Rapid Capabilities and Critical Technologies Office. The team consists of additional members from the laboratory's Airborne Radar Systems and Techniques, Integrated RF and Photonics, Mechanical Engineering, Advanced Capabilities and Systems, Homeland Protection Systems, and Transportation Safety and Resilience groups.

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a novel artificial intelligence model inspired by neural oscillations in the brain, with the goal of significantly advancing how machine learning algorithms handle long sequences of data.

AI often struggles with analyzing complex information that unfolds over long periods of time, such as climate trends, biological signals, or financial data. One new type of AI model, called "state-space models," has been designed specifically to understand these sequential patterns more effectively. However, existing state-space models often face challenges — they can become unstable or require a significant amount of computational resources when processing long data sequences.

To address these issues, CSAIL researchers T. Konstantin Rusch and Daniela Rus have developed what they call “linear oscillatory state-space models” (LinOSS), which leverage principles of forced harmonic oscillators — a concept deeply rooted in physics and observed in biological neural networks. This approach provides stable, expressive, and computationally efficient predictions without overly restrictive conditions on the model parameters.

"Our goal was to capture the stability and efficiency seen in biological neural systems and translate these principles into a machine learning framework," explains Rusch. "With LinOSS, we can now reliably learn long-range interactions, even in sequences spanning hundreds of thousands of data points or more."

The LinOSS model is unique in ensuring stable prediction by requiring far less restrictive design choices than previous methods. Moreover, the researchers rigorously proved the model’s universal approximation capability, meaning it can approximate any continuous, causal function relating input and output sequences.

Empirical testing demonstrated that LinOSS consistently outperformed existing state-of-the-art models across various demanding sequence classification and forecasting tasks. Notably, LinOSS outperformed the widely-used Mamba model by nearly two times in tasks involving sequences of extreme length.

Recognized for its significance, the research was selected for an oral presentation at ICLR 2025 — an honor awarded to only the top 1 percent of submissions. The MIT researchers anticipate that the LinOSS model could significantly impact any fields that would benefit from accurate and efficient long-horizon forecasting and classification, including health-care analytics, climate science, autonomous driving, and financial forecasting.

"This work exemplifies how mathematical rigor can lead to performance breakthroughs and broad applications," Rus says. "With LinOSS, we’re providing the scientific community with a powerful tool for understanding and predicting complex systems, bridging the gap between biological inspiration and computational innovation."

The team imagines that the emergence of a new paradigm like LinOSS will be of interest to machine learning practitioners to build upon. Looking ahead, the researchers plan to apply their model to an even wider range of different data modalities. Moreover, they suggest that LinOSS could provide valuable insights into neuroscience, potentially deepening our understanding of the brain itself.

Their work was supported by the Swiss National Science Foundation, the Schmidt AI2050 program, and the U.S. Department of the Air Force Artificial Intelligence Accelerator.

In the dim light of the lab, friends, family, and strangers watched the image of a pianist playing for them, the pianist’s fingers projected onto the moving keys of a real grand piano that filled the space with music.

Watching the ghostly musicians, faces and bodies blurred at their edges, several listeners shared one strong but strange conviction: “feeling someone’s presence” while “also knowing that I am the only one in the room.”

“It’s tough to explain,” another listener said. “It felt like they were in the room with me, but at the same time, not.”

That presence of absence is at the heart of TeleAbsence, a project by the MIT Media Lab’s Tangible Media group that focuses on technologies that create illusory communication with the dead and with past selves.

But rather than a “Black Mirror”-type scenario of synthesizing literal loved ones, the project led by Hiroshi Ishii, the Jerome B. Wiesner Professor of Media Arts and Sciences, instead seeks what it calls “poetic encounters” that reach across time and memory.

The project recently published a positioning paper in PRESENCE: Virtual and Augmented Reality that presents the design principles behind TeleAbsence, and how it could help people cope with loss and plan for how they might be remembered.

The phantom pianists of the MirrorFugue project, created by Tangible Media graduate Xiao Xiao ’09, SM ’11, PhD ’16, are one of the best-known examples of the project. On April 30, Xiao, now director and principal investigator at the Institute for Future Technologies of Da Vinci Higher Education in Paris, shared results from the first experimental study of TeleAbsence through MirrorFugue at the 2025 CHI conference on Human Factors in Computing Systems in Yokohama, Japan.

When Ishii spoke about TeleAbsence at the XPANSE 2024 conference in Abu Dhabi, “about 20 people came up to me after, and all of them told me they had tears in their eyes … the talk reminded them about a wife or a father who passed away,” he says. “One thing is clear: They want to see them again and talk to them again, metaphorically.”

Messages in bottles

As the director of the Tangible Media group, Ishii has been a world leader in telepresence, using technologies to connect people over physical distance. But when his mother died in 1998, Ishii says the pain of the loss prompted him to think about how much we long to connect across the distance of time.

His mother wrote poetry, and one of his first experiments in TeleAbsence was the creation of a Twitterbot that would post snippets of her poetry. Others watching the account online were so moved that they began posting photos of flowers to the feed to honor the mother and son.

“That was a turning point for TeleAbsence, and I wanted to expand this concept,” Ishii says.

Illusory communication, like the posted poems, is one key design principle of TeleAbsence. Even though users know the “conversation” is one-way, the researchers write, it can be comforting and cathartic to have a tangible way to reach out across time.

Finding ways to make memories material is another important design principle. One of the projects created by Ishii and colleagues is a series of glass bottles, reminiscent of the soy sauce bottles Ishii’s mother used while cooking. Open one of the bottles, and the sounds of chopping, of sizzling onions, of a radio playing quietly in the background, of a maternal voice, reunite a son with his mother.

Ishii says sight and sound are the primary modalities of TeleAbsence technologies for now, because although the senses of touch, smell, and taste are known to be powerful memory triggers, “it is a very big challenge to record that kind of multimodal moment.”

At the same time, one of the other pillars of TeleAbsence is the presence of absence. These are the physical markers, or traces, of a person that serve to remind us both of the person and that the person is gone. One of the most powerful examples, the researchers write, is the permanent “shadow” of Hiroshima Japanese resident Mitsuno Ochi, her silhouette transferred to stone steps 260 meters from where the atomic bomb detonated in 1945.

“Abstraction is very important,” Ishii says. “We want something to recall a moment, not physically recreate it.”

With the bottles, for instance, people have asked Ishii and his colleagues whether it might be more evocative to fill them with a perfume or drink. “But our philosophy is to make a bottle completely empty,” he explains. “The most important thing to let people imagine, based on the memory.”

Other important design principles within TeleAbsence include traces of reflection — the ephemera of faint pen scratches and blotted ink on a preserved letter, for instance — and the concept of remote time. TeleAbsence should go beyond dredging up a memory of a loved one, the researchers insist, and should instead produce a sense of being transported to spend a moment in the past with them.

Time travelers

For Xiao, who has played the piano her whole life, MirrorFugue is a “deeply personal project” that allowed her to travel to a time in her childhood that was almost lost to her.

Her parents moved from China to the United States when she was a baby — but it took eight years for Xiao to follow. “The piano, in a sense, was almost like my first language,” she recalls. “And then when I moved to America, my brain overwrote bits of my childhood where my operating system used to be in Chinese, and now it’s very much in English. But throughout this whole time, music and the piano stayed constant.”

MirrorFugue’s “sense of kind-of being there and not being there, and the wish to connect with oneself from the past, comes from my own desire to connect with my own past self,” she adds.

The new MirrorFugue study puts some empirical data behind the concept of TeleAbsence, she says. Its 28 participants were fitted with sensors to measure changes in their heart rate and hand movements during the experience. They were extensively interviewed about their perceptions and emotions afterward. The recorded images came from pianists ranging in experience from children early in their lessons to professional pianists like the late Ryuichi Sakamoto.

The researchers found that emotional experiences described by the listeners were significantly influenced by whether the listeners knew the pianist, as well as whether the pianist was known by the listeners to be alive or dead.

Some participants placed their own hands alongside the ghosts to play impromptu duets. One daughter, who said she had not paid close attention to her father’s playing when he was alive, was newly impressed by his talent. One person felt empathy watching his past self struggle through a new piece of music. A young girl, mouth slightly open in concentration and fingers small on the keys, showed her mother a past daughter that wasn’t possible to see in old photos.

The longing for past people and past selves can be “a deep sadness that will never go away,” says Xiao. “You’ll always carry it with you, but it also makes you sensitive to certain aesthetic experiences that’s also beautiful.”

“Once you’ve had that experience, it really resonates,” she adds, “And I think that’s why TeleAbsence resonates with so many people.”

Uncanny valleys and curated memory

Acutely aware of the potential ethical dangers of their research, the TeleAbsence scientists have worked with grief researchers and psychologists to better understand the implications of building these bridges through time.

For instance, “one thing we learned is that it depends on how long ago a person passed away,” says Ishii. “Right after death, when it’s very difficult for many people, this representation matters. But you have to make important informed decisions about whether this drags out the grief too long.”

TeleAbsence could comfort the dying, he says, by “knowing there is a means by which they are going to live on for their descendants.” He encourages people to consider curating “high-quality, condensed information,” such as their social media posts, that could be used for this purpose.

“But of course many families do not have ideal relationships, so I can easily think of the case where a descendant might not have any interest” in interacting with their ancestors through TeleAbsence, Ishii notes.

TeleAbsence should never fully recreate or generate new content for a loved one, he insists, pointing to the rise of “ghost bot” startups, companies that collect data on a person to create an “artificial, generative AI-based avatar that speaks what they never spoke, or do gestures or facial expressions.”

A recent viral video of a mother in Korea “reunited” in virtual reality with an avatar of her dead daughter, Ishii says, made him “very depressed, because they’re doing grief as entertainment, consumption for an audience.”

Xiao thinks there might still be some role for generative AI in the TeleAbsence space. She is writing a research proposal for MirrorFugue that would include representations of past pianists. “I think right now we’re getting to the point with generative AI that we can generate hand movements and we can transcribe the MIDI from the audio so that we can conjure up Franz Listz or Mozart or somebody, a really historical figure.”

“Now of course, it gets a little bit tricky, and we have discussed this, the role of AI and how to avoid the uncanny valley, how to avoid deceiving people,” she says. “But from a researcher’s perspective, it actually excites me a lot, the possibility to be able to empirically test these things.”

The importance of emptiness

Along with Ishii’s mother, the PRESENCE paper was also dedicated “in loving memory” to Elise O’Hara, a beloved Media Lab administrative assistant who worked with Tangible Media until her unexpected death in 2023. Her presence — and her absence — are felt deeply every day, says Ishii.

He wonders if TeleAbsence could someday become a common word “to describe something that was there, but is now gone.”

“When there is a place on a bookshelf where a book should be,” he says, “my students say, ‘oh, that’s a teleabsence.’”

Like a sudden silence in the middle of a song, or the empty white space of a painting, emptiness can hold important meaning. It’s an idea that we should make more room for in our lives, Ishii says.

“Because now we’re so busy, so many notification messages from your smartphone, and we are all distracted, always,” he suggests. “So emptiness and impermanence, presence of absence, if those concepts can be accepted, then people can think a bit more poetically.”

The composition of bacterial populations living on our faces plays a significant role in the development of acne and other skin conditions such as eczema. Two species of bacteria predominate in most people, but how they interact with each other, and how those interactions may contribute to disease, has been difficult to study.

MIT researchers have now revealed the dynamics of those interactions in more detail than previously possible, shedding light on when and how new bacterial strains emerge on the skin of the face. Their findings could help guide the development of new treatments for acne and other conditions, and may also help to optimize the timing of such treatments.

The researchers found that many new strains of Cutibacterium acnes, a species believed to contribute to the development of acne, are acquired during the early teenage years. But after that, the makeup of these populations becomes very stable and doesn’t change much even when exposed to new strains.

That suggests that this transitional stage could be the best window for introducing probiotic strains of C. acnes, says Tami Lieberman, an associate professor of civil and environmental engineering, a member of MIT’s Institute for Medical Engineering and Science, and the senior author of the study.

“We found that there are some surprising dynamics, and these dynamics provide insights for how to design probiotic therapy,” Lieberman says. “If we had a strain that we knew could prevent acne, these results would suggest we should make sure we apply them early during the transition to adulthood, to really get them to engraft.”

Jacob Baker PhD ’24, who is now the chief scientific officer at Taxa Technologies, is the lead author of the paper, which appears today in Cell Host and Microbe. Other authors include MIT graduate student Evan Qu, MIT postdoc Christopher Mancuso, Harvard University graduate student A. Delphine Tripp, and former MIT postdoc Arolyn Conwill PhD ’18.

Microbial dynamics

Although C. acnes has been implicated in the development of acne, it is still unclear exactly why acne develops in some people but not others — it may be that some strains are more likely to cause skin inflammation, or there may be differences in how the host immune system responds to the bacteria, Lieberman says. There are probiotic strains of C. acnes now available, which are thought to help prevent acne, but the benefits of these strains have not been proven.

Along with C. acnes, the other predominant bacterium found on the face is Staphylococcus epidermidis. Together, these two strains make up about 80 percent of the strains in the adult facial skin microbiome. Both of these species exist in different strains, or lineages, that vary by a small number of genetic mutations. However, until now, researchers had not been able to accurately measure this diversity or track how it changes over time.

Learning more about those dynamics could help researchers answer key questions that could help them develop new probiotic treatments for acne: How easy is it for new lineages to establish themselves on the skin, and what is the best time to introduce them?

To study these population shifts, the researchers had to measure how individual cells evolve over time. To do that, they began by obtaining microbiome samples from 30 children at a Boston-area school and from 27 of their parents. Studying members of the same family enabled the researchers to analyze the likelihood of different lineages being transferred between people in close contact.

For about half of the individuals, the researchers were able to take samples at multiple time points, and for the rest, only once. For each sample, they isolated individual cells and grew them into colonies, then sequenced their genomes.

This allowed the researchers to learn how many lineages were found on each person, how they changed over time, and how different cells from the same lineage were. From that information, the researchers could infer what had happened to those lineages in the recent past and how long they had been present on the individual.

Overall, the researchers identified a total of 89 C. acnes lineages and 78 S. epidermidis lineages, with up to 11 of each found in each person’s microbiome. Previous work had suggested that in each person’s facial skin microbiome, lineages of these two skin bacteria remain stable over long periods of time, but the MIT team found that these populations are actually more dynamic than previously thought.

“We wanted to know if these communities were truly stable, and if there could be times where they weren’t stable. In particular, if the transition to an adult skin like microbiome would have a higher rate of acquisition of new lineages,” Lieberman says.

During the early teens, an increase in hormone production results in increased oil on the skin, which is a good food source for bacteria. It has previously been shown that during this time, the density of bacteria on the skin of the face increases by about 10,000-fold. In this study, the researchers found that while the composition of C. acnes populations tended to remain very stable over time, the early teenage years present an opportunity for many more lineages of C. acnes to appear.

“For C. acnes, what we were able to show was that people do get strains throughout life, but very rarely,” Lieberman says. “We see the highest rate of influx when teenagers are transitioning to a more adult-like skin microbiome.”

The findings suggest that for topical probiotic treatments for acne, the best time to apply them is during the early teenage years, when there could be more opportunity for probiotic strains to become established.

Population turnover

Later in adulthood, there is a little bit of sharing of C. acnes strains between parents living in the same household, but the rate of turnover in any individual person’s microbiome is still very low, Lieberman says.

The researchers found that S. epidermidis has a much higher turnover rate than C. acnes — each S. epidermidis strain lives on the face for an average of less than two years. However, there was not very much overlap in the S. epidermidis lineages shared by members of the same household, suggesting that transfer of strains between people is not causing the high turnover rate.

“That suggests that something is preventing homogenization between people,” Lieberman says. “It could be host genetics or host behavior, or people using different topicals or different moisturizers, or it could be active restriction of new migrants from the bacteria that are already there at that moment.”

Now that they’ve shown that new C. acnes strains can be acquired during the early teenage years, the researchers hope to study whether the timing of this acquisition affects how the immune system responds to them. They also hope to learn more about how people maintain such different microbiome populations even when exposed to new lineages through close contact with family members.

“We want to understand why we each have unique strain communities despite the fact that there is this constant accessibility and high turnover, specifically for S. epidermidis,” Lieberman says. “What’s driving this constant turnover in S. epidermidis, and what are the implications of these new colonizations for acne during adolescence?”

The research was funded by the MIT Center for Microbiome Informatics and Therapeutics, a Smith Family Foundation Award for Excellence in Biomedical Research, and the National Institutes of Health.

The ambiguity in medical imaging can present major challenges for clinicians who are trying to identify disease. For instance, in a chest X-ray, pleural effusion, an abnormal buildup of fluid in the lungs, can look very much like pulmonary infiltrates, which are accumulations of pus or blood.

An artificial intelligence model could assist the clinician in X-ray analysis by helping to identify subtle details and boosting the efficiency of the diagnosis process. But because so many possible conditions could be present in one image, the clinician would likely want to consider a set of possibilities, rather than only having one AI prediction to evaluate.

One promising way to produce a set of possibilities, called conformal classification, is convenient because it can be readily implemented on top of an existing machine-learning model. However, it can produce sets that are impractically large. 

MIT researchers have now developed a simple and effective improvement that can reduce the size of prediction sets by up to 30 percent while also making predictions more reliable.

Having a smaller prediction set may help a clinician zero in on the right diagnosis more efficiently, which could improve and streamline treatment for patients. This method could be useful across a range of classification tasks — say, for identifying the species of an animal in an image from a wildlife park — as it provides a smaller but more accurate set of options.

“With fewer classes to consider, the sets of predictions are naturally more informative in that you are choosing between fewer options. In a sense, you are not really sacrificing anything in terms of accuracy for something that is more informative,” says Divya Shanmugam PhD ’24, a postdoc at Cornell Tech who conducted this research while she was an MIT graduate student.

Shanmugam is joined on the paper by Helen Lu ’24; Swami Sankaranarayanan, a former MIT postdoc who is now a research scientist at Lilia Biosciences; and senior author John Guttag, the Dugald C. Jackson Professor of Computer Science and Electrical Engineering at MIT and a member of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). The research will be presented at the Conference on Computer Vision and Pattern Recognition in June.

Prediction guarantees

AI assistants deployed for high-stakes tasks, like classifying diseases in medical images, are typically designed to produce a probability score along with each prediction so a user can gauge the model’s confidence. For instance, a model might predict that there is a 20 percent chance an image corresponds to a particular diagnosis, like pleurisy.

But it is difficult to trust a model’s predicted confidence because much prior research has shown that these probabilities can be inaccurate. With conformal classification, the model’s prediction is replaced by a set of the most probable diagnoses along with a guarantee that the correct diagnosis is somewhere in the set.

But the inherent uncertainty in AI predictions often causes the model to output sets that are far too large to be useful.

For instance, if a model is classifying an animal in an image as one of 10,000 potential species, it might output a set of 200 predictions so it can offer a strong guarantee.

“That is quite a few classes for someone to sift through to figure out what the right class is,” Shanmugam says.

The technique can also be unreliable because tiny changes to inputs, like slightly rotating an image, can yield entirely different sets of predictions.

To make conformal classification more useful, the researchers applied a technique developed to improve the accuracy of computer vision models called test-time augmentation (TTA).

TTA creates multiple augmentations of a single image in a dataset, perhaps by cropping the image, flipping it, zooming in, etc. Then it applies a computer vision model to each version of the same image and aggregates its predictions.

“In this way, you get multiple predictions from a single example. Aggregating predictions in this way improves predictions in terms of accuracy and robustness,” Shanmugam explains.

Maximizing accuracy

To apply TTA, the researchers hold out some labeled image data used for the conformal classification process. They learn to aggregate the augmentations on these held-out data, automatically augmenting the images in a way that maximizes the accuracy of the underlying model’s predictions.

Then they run conformal classification on the model’s new, TTA-transformed predictions. The conformal classifier outputs a smaller set of probable predictions for the same confidence guarantee.

“Combining test-time augmentation with conformal prediction is simple to implement, effective in practice, and requires no model retraining,” Shanmugam says.

Compared to prior work in conformal prediction across several standard image classification benchmarks, their TTA-augmented method reduced prediction set sizes across experiments, from 10 to 30 percent.

Importantly, the technique achieves this reduction in prediction set size while maintaining the probability guarantee.

The researchers also found that, even though they are sacrificing some labeled data that would normally be used for the conformal classification procedure, TTA boosts accuracy enough to outweigh the cost of losing those data.

“It raises interesting questions about how we used labeled data after model training. The allocation of labeled data between different post-training steps is an important direction for future work,” Shanmugam says.

In the future, the researchers want to validate the effectiveness of such an approach in the context of models that classify text instead of images. To further improve the work, the researchers are also considering ways to reduce the amount of computation required for TTA.

This research is funded, in part, by the Wistrom Corporation.

For policymakers investigating the effective transition of an economy from agriculture to manufacturing and services, there are complex economic, institutional, and practical considerations. “Are certain regions trapped in an under-industrialization state?” asks Tishara Garg, an economics doctoral student at MIT. “If so, can government policy help them escape this trap and transition to an economy characterized by higher levels of industrialization and better-paying jobs?” 

Garg’s research focuses on trade, economic geography, and development. Her studies yielded the paper “Can Industrial Policy Overcome Coordination Failures: Theory and Evidence from Industrial Zones,” which investigates whether economic policy can shift an economy from an undesirable state to a desirable state. 

Garg’s work combines tools from industrial organization and numerical algebraic geometry. Her paper finds that regions in India with state-developed industrial zones are 38 percent more likely to shift from a low to high industrialization state over a 15-year period than those without such zones.  

The kinds of questions uncovered during her studies aren’t easily answered using standard technical and econometric tools, so she’s developing new ones. “One of my study’s main contributions is a methodological framework that draws on ideas from different areas,” she notes. “These tools not only help me study the question I want to answer, but are also general enough to help study a broader set of questions around multiple challenges.”

The new tools she’s developed, along with a willingness to engage with other disciplines, have helped her discover innovative ways to approach these challenges while learning to work with new ones, options she asserts are actively encouraged at an institution like MIT.

“I benefited from having an open mind and learning different things,” she says.

“I was introduced to academia late”

Garg’s journey from Kaithal, India, to MIT wasn’t especially smooth, as societal pressures exerted a powerful influence. “The traditional path for someone like me is to finish school, enter an arranged marriage, and start a family,” she says. “But I was good at school and wanted to do more.” 

Garg, who hails from a background with limited access to information on career development opportunities, took to math early. “I chose business in high school because I planned to become an accountant,” she recalls. “My uncle was an accountant.”

While pursuing the successful completion of a high school business track, she became interested in economics. “I didn’t know much about economics, but I came to enjoy it,” she says. Garg relishes the pursuit of deductive reasoning that begins with a set of assumptions and builds, step by step, toward a well-defined, clear conclusion. She especially enjoys grappling with the arguments she found in textbooks. She continued to study economics as an undergraduate at the University of Delhi, and later earned her master’s from the Indian Statistical Institute. Doctoral study wasn’t an option until she made it one.

“It took me some time to convince my parents,” she says. She spent a year at a hedge fund before applying to economics doctoral programs in the United States and choosing MIT. “I was introduced to academia late,” she notes. “But my heart was being drawn to the academic path.”

Answering ambitious and important questions

Garg, who hadn’t left India before her arrival in Cambridge, Massachusetts, found the transition challenging. “There were new cultural norms, a language barrier, different foods, and no preexisting social network,” she says. Garg relied on friends and MIT faculty for support when she arrived in 2019. 

“When Covid hit, the department looked out for me,” she says. Garg recalls regular check-ins from a faculty advisor and the kind of camaraderie that can grow from shared circumstances, like Covid-related sheltering protocols. A world that forced her to successfully navigate a new and unfamiliar reality helped reshape how she viewed herself. “Support from the community at MIT helped me grow in many ways,” she recalls, “I found my voice here.”

Once she began her studies, one of the major differences Garg found was the diversity of opinions in her field of inquiry. “At MIT, I could speak with students and faculty specializing in trade, development economics, industrial organization, macroeconomics, and more,” she says. “I had limited exposure to many of these subfields before coming to MIT.” 

She quickly found her footing, leaning heavily on both her past successes and the academic habits she developed during her studies in India. “I’m not a passive learner,” she says. “My style is active, critical, and engaged.”

Conducting her research exposes Garg to new ideas. She learned the value of exploring other disciplines’ approaches to problem-solving, which was encouraged and enabled at MIT. 

One of the classes she came to enjoy most was a course in industrial organization taught by Tobias Salz. “I had little familiarity with the material, and it was highly technical — but he taught it in such a clear and intuitive way that I found myself truly enjoying the class, even though it was held during the pandemic,” she recalls. That early experience laid the groundwork for future research. Salz went on to advise her dissertation, helping her engage with work she would build upon.

“Answering ambitious and important questions is what draws me to the work,” Garg says. “I enjoy learning, I enjoy the creative process of bringing different ideas together and MIT's environment has made it easy for me to pick up new things.”

Working with her advisors at MIT helped Garg formalize her research and appreciate the value of uncovering questions and developing approaches to answer them. Professor Abhijit Banerjee, an advisor and Nobel laureate, helped her understand the importance of appreciating different traditions while also staying true to how you think about the problem, she recalls. “That gave me the confidence to pursue the questions in ways that felt most compelling and personal to me,” she says, “even if they didn’t fit neatly into disciplinary boundaries.”

This encouragement, combined with the breadth of perspectives at MIT, pushed her to think creatively about research challenges and to look beyond traditional tools to discover solutions. “MIT’s faculty have helped me improve the way I think and refine my approach to this work,” she says.

Paying it forward

Garg, who will continue her research as a postdoc at Princeton University in the fall and begin her career as a professor at Stanford University in 2026, singles out her network of friends and advisors for special praise.

“From regular check-ins with my advisors to the relationships that help me find balance with my studies, the people at MIT have been invaluable,” she says. 

Garg is especially invested in mentorship opportunities available as a researcher and professor. “I benefited from the network of friends and mentors at MIT and I want to pay it forward — especially for women, and others from backgrounds like mine,” she says.

She cites the work of her advisors, David Atkin and Dave Donaldson — with whom she is also collaborating on research studying incidences of economic distortions — as both major influences on her development and a key reason she’s committed to mentoring others. “They’ve been with me every step of the way,” she says. 

Garg recommends keeping an open mind, above all. “Some of my students didn’t come from a math-heavy background and would restrict themselves or otherwise get discouraged from pursuing theoretical work,” she says. “But I always encouraged them to pursue their interests above all, even if it scared them.” 

The variety of ideas available in her area of inquiry still fascinates Garg, who’s excited about what’s next. “Don’t shy from big questions,” she says. “Explore the big idea.”

With war continuing to disrupt education for millions of Ukrainian high school and college students, many are turning to online resources, including MIT OpenCourseWare, a part of MIT Open Learning offering educational materials from more than 2,500 MIT undergraduate and graduate courses.

For Ukrainian high school senior Sofiia Lipkevych and other students, MIT OpenCourseWare has provided valuable opportunities to take courses in key subject areas. However, while multiple Ukrainian students study English, many do not yet have sufficient command of the language to be able to fully understand and use the often very technical and complex OpenCourseWare content and materials.

“At my school, I saw firsthand how language barriers prevented many Ukrainian students from accessing world-class education,” says Lipkevych.

She was able to address this challenge as a participant in the Ukrainian Leadership and Technology Academy (ULTA), established by Ukrainian MIT students Dima Yanovsky and Andrii Zahorodnii. During summer 2024 at ULTA, Lipkevych worked on a browser extension that translated YouTube videos in real-time. Since MIT OpenCourseWare was a main source of learning materials for students participating in ULTA, she was inspired to translate OpenCourseWare lectures directly and to have this translation widely available on the OpenCourseWare website and YouTube channel. She reached out to Professor Elizabeth Wood, founding director of the MIT Ukraine Program, who connected her with MIT OpenCourseWare Director Curt Newton.

Although there had been some translations of MIT OpenCourseWare’s educational resources available beginning in 2004, these initial translations were conducted manually by several global partners, without the efficiencies of the latest artificial intelligence tools, and over time the programs couldn’t be sustained, and shut down.

“We were thrilled to have this contact with ULTA,” says Newton. “We’ve been missing having a vibrant translation community, and we are excited to have a ‘phase 2’ of translations emerge.”

The ULTA team selected courses to translate based on demand among Ukrainian students, focusing on foundational subjects that are prerequisites for advanced learning — particularly those for which high-quality, Ukrainian-language materials are scarce. Starting with caption translations on videos of lectures, the team has translated the following courses so far: 18.06 (Linear Algebra), 2.003SC (Engineering Dynamics), 5.60 (Thermodynamics & Kinetics), 6.006 (Introduction to Algorithms), and 6.0001 (Introduction to Computer Science and Programming in Python). They also worked directly with Andy Eskenazi, a PhD student in the MIT Department of Aeronautics and Astronautics, to translate 16.002 (How to CAD Almost Anything - Siemens NX Edition).

The ULTA team developed multiple tools to help break language barriers. For MIT OpenCourseWare’s PDF content available through the ULTA program, they created a specialized tool that uses optical character recognition to recognize LaTeX in documents — such as problem sets and other materials — and then used a few large language models to translate them, all while maintaining technical accuracy. The team built a glossary of technical terms used in the courses and their corresponding Ukrainian translations, to help make sure that the wording was correct and consistent. Each translation also undergoes human review to further ensure accuracy and high quality.

For video content, the team initially created a browser extension that can translate YouTube video captions in real-time. They ultimately collaborated with ElevenLabs, implementing their advanced AI dubbing editor that preserves the original speaker's tone, pace, and emotional delivery. The lectures are translated in the ElevenLabs dubbing editor, and then the audio is uploaded to the MIT OpenCourseWare YouTube channel.

The team is currently finalizing the translation of the audio for class 9.13 (The Human Brain), taught by MIT Professor Nancy Kanwisher, which Lipkevych says they selected for its interdisciplinary nature and appeal to a wide variety of learners.

This Ukrainian translation project highlights the transformative potential of the latest translation technologies, building upon a 2023 MIT OpenCourseWare experiment using the Google Aloud AI dubbing prototype on a few courses, including MIT Professor Patrick Winston’s How to Speak. The advanced capabilities of the dubbing editor used in this project are opening up possibilities for a much greater variety of language offerings throughout MIT OpenCourseWare materials.

“I expect that in a few years we’ll look back and see that this was the moment when things shifted for OpenCourseWare to be truly usable for the whole world,” says Newton.

Community-led language translations of MIT OpenCourseWare materials serve as a high-impact example of the power of OpenCourseWare’s Creative Commons licensing, which grants everyone the right to revise materials to suit their particular needs and redistribute those revisions to the world.

While there isn’t currently a way for users of the MIT OpenCourseWare platform to quickly identify which videos are available in which languages, MIT OpenCourseWare is working toward building this capability into its website, as well as expanding its number of offerings in different languages.

“This project represents more than just translation,” says Lipkevych. “We’re enabling thousands of Ukrainians to build skills that will be essential for the country’s eventual reconstruction. We’re also hoping this model of collaboration can be extended to other languages and institutions, creating a template for making high-quality education accessible worldwide.”

Since its founding 19 years ago as a pioneering collaboration with Portuguese universities, research institutions and corporations, the MIT-Portugal Program (MPP) has achieved a slew of successes — from enabling 47 entrepreneurial spinoffs and funding over 220 joint projects between MIT and Portuguese researchers to training a generation of exceptional researchers on both sides of the Atlantic.

In March, with nearly two decades of collaboration under their belts, MIT and the Portuguese Science and Technology Foundation (FCT) signed an agreement that officially launches the program’s next chapter. Running through 2030, MPP’s Phase 4 will support continued exploration of innovative ideas and solutions in fields ranging from artificial intelligence and nanotechnology to climate change — both on the MIT campus and with partners throughout Portugal.  

“One of the advantages of having a program that has gone on so long is that we are pretty well familiar with each other at this point. Over the years, we’ve learned each other’s systems, strengths and weaknesses and we’ve been able to create a synergy that would not have existed if we worked together for a short period of time,” says Douglas Hart, MIT mechanical engineering professor and MPP co-director.

Hart and John Hansman, the T. Wilson Professor of Aeronautics and Astronautics at MIT and MPP co-director, are eager to take the program’s existing research projects further, while adding new areas of focus identified by MIT and FCT. Known as the Fundação para a Ciência e Tecnologia in Portugal, FCT is the national public agency supporting research in science, technology and innovation under Portugal’s Ministry of Education, Science and Innovation.

“Over the past two decades, the partnership with MIT has built a foundation of trust that has fostered collaboration among researchers and the development of projects with significant scientific impact and contributions to the Portuguese economy,” Fernando Alexandre, Portugal’s minister for education, science, and innovation, says. “In this new phase of the partnership, running from 2025 to 2030, we expect even greater ambition and impact — raising Portuguese science and its capacity to transform the economy and improve our society to even higher levels, while helping to address the challenges we face in areas such as climate change and the oceans, digitalization, and space.”

“International collaborations like the MIT-Portugal Program are absolutely vital to MIT’s mission of research, education and service. I’m thrilled to see the program move into its next phase,” says MIT President Sally Kornbluth. “MPP offers our faculty and students opportunities to work in unique research environments where they not only make new findings and learn new methods but also contribute to solving urgent local and global problems. MPP’s work in the realm of ocean science and climate is a prime example of how international partnerships like this can help solve important human problems."

Sharing MIT’s commitment to academic independence and excellence, Kornbluth adds, “the institutions and researchers we partner with through MPP enhance MIT’s ability to achieve its mission, enabling us to pursue the exacting standards of intellectual and creative distinction that make MIT a cradle of innovation and world leader in scientific discovery.”

The epitome of an effective international collaboration, MPP has stayed true to its mission and continued to deliver results here in the U.S. and in Portugal for nearly two decades — prevailing amid myriad shifts in the political, social, and economic landscape. The multifaceted program encompasses an annual research conference and educational summits such as an Innovation Workshop at MIT each June and a Marine Robotics Summer School in the Azores in July, as well as student and faculty exchanges that facilitate collaborative research. During the third phase of the program alone, 59 MIT students and 53 faculty and researchers visited Portugal, and MIT hosted 131 students and 49 faculty and researchers from Portuguese universities and other institutions.

In each roughly five-year phase, MPP researchers focus on a handful of core research areas. For Phase 3, MPP advanced cutting-edge research in four strategic areas: climate science and climate change; Earth systems: oceans to near space; digital transformation in manufacturing; and sustainable cities. Within these broad areas, MIT and FCT researchers worked together on numerous small-scale projects and several large “flagship” ones, including development of Portugal’s CubeSat satellite, a collaboration between MPP and several Portuguese universities and companies that marked the country’s second satellite launch and the first in 30 years.

While work in the Phase 3 fields will continue during Phase 4, researchers will also turn their attention to four more areas: chips/nanotechnology, energy (a previous focus in Phase 2), artificial intelligence, and space.

“We are opening up the aperture for additional collaboration areas,” Hansman says.

In addition to focusing on distinct subject areas, each phase has emphasized the various parts of MPP’s mission to differing degrees. While Phase 3 accentuated collaborative research more than educational exchanges and entrepreneurship, those two aspects will be given more weight under the Phase 4 agreement, Hart said.

“We have approval in Phase 4 to bring a number of Portuguese students over, and our principal investigators will benefit from close collaborations with Portuguese researchers,” he says.

The longevity of MPP and the recent launch of Phase 4 are evidence of the program’s value. The program has played a role in the educational, technological and economic progress Portugal has achieved over the past two decades, as well.  

“The Portugal of today is remarkably stronger than the Portugal of 20 years ago, and many of the places where they are stronger have been impacted by the program,” says Hansman, pointing to sustainable cities and “green” energy, in particular. “We can’t take direct credit, but we’ve been part of Portugal’s journey forward.”

Since MPP began, Hart adds, “Portugal has become much more entrepreneurial. Many, many, many more start-up companies are coming out of Portuguese universities than there used to be.”  

A recent analysis of MPP and FCT’s other U.S. collaborations highlighted a number of positive outcomes. The report noted that collaborations with MIT and other US universities have enhanced Portuguese research capacities and promoted organizational upgrades in the national R&D ecosystem, while providing Portuguese universities and companies with opportunities to engage in complex projects that would have been difficult to undertake on their own.

Regarding MIT in particular, the report found that MPP’s long-term collaboration has spawned the establishment of sustained doctoral programs and pointed to a marked shift within Portugal’s educational ecosystem toward globally aligned standards. MPP, it reported, has facilitated the education of 198 Portuguese PhDs.

Portugal’s universities, students and companies are not alone in benefitting from the research, networks, and economic activity MPP has spawned. MPP also delivers unique value to MIT, as well as to the broader US science and research community. Among the program’s consistent themes over the years, for example, is “joint interest in the Atlantic,” Hansman says.

This summer, Faial Island in the Azores will host MPP’s fifth annual Marine Robotics Summer School, a two-week course open to 12 Portuguese Master’s and first year PhD students and 12 MIT upper-level undergraduates and graduate students. The course, which includes lectures by MIT and Portuguese faculty and other researchers, workshops, labs and hands-on experiences, “is always my favorite,” said Hart.

“I get to work with some of the best researchers in the world there, and some of the top students coming out of Woods Hole Oceanographic Institution, MIT, and Portugal,” he says, adding that some of his previous Marine Robotics Summer School students have come to study at MIT and then gone on to become professors in ocean science.

“So, it’s been exciting to see the growth of students coming out of that program, certainly a positive impact,” Hart says.

MPP provides one-of-a-kind opportunities for ocean research due to the unique marine facilities available in Portugal, including not only open ocean off the Azores but also Lisbon’s deep-water port and a Portuguese Naval facility just south of Lisbon that is available for collaborative research by international scientists. Like MIT, Portuguese universities are also strongly invested in climate change research — a field of study keenly related to ocean systems.

“The international collaboration has allowed us to test and further develop our research prototypes in different aquaculture environments both in the US and in Portugal, while building on the unique expertise of our Portuguese faculty collaborator Dr. Ricardo Calado from the University of Aveiro and our industry collaborators,” says Stefanie Mueller, the TIBCO Career Development Associate Professor in MIT’s departments of Electrical Engineering and Computer Science and Mechanical Engineering and leader of the Human-Computer Interaction Group at the MIT Computer Science and Artificial Intelligence Lab.

Mueller points to the work of MIT mechanical engineering PhD student Charlene Xia, a Marine Robotics Summer School participant, whose research is aimed at developing an economical system to monitor the microbiome of seaweed farms and halt the spread of harmful bacteria associated with ocean warming. In addition to participating in the summer school as a student, Xia returned to the Azores for two subsequent years as a teaching assistant.

“The MIT-Portugal Program has been a key enabler of our research on monitoring the aquatic microbiome for potential disease outbreaks,” Mueller says.

As MPP enters its next phase, Hart and Hansman are optimistic about the program’s continuing success on both sides of the Atlantic and envision broadening its impact going forward.

“I think, at this point, the research is going really well, and we’ve got a lot of connections. I think one of our goals is to expand not the science of the program necessarily, but the groups involved,” Hart says, noting that MPP could have a bigger presence in technical fields such as AI and micro-nano manufacturing, as well as in social sciences and humanities.

“We’d like to involve many more people and new people here at MIT, as well as in Portugal,” he says, “so that we can reach a larger slice of the population.” 

In the future, quantum computers could rapidly simulate new materials or help scientists develop faster machine-learning models, opening the door to many new possibilities.

But these applications will only be possible if quantum computers can perform operations extremely quickly, so scientists can make measurements and perform corrections before compounding error rates reduce their accuracy and reliability.

The efficiency of this measurement process, known as readout, relies on the strength of the coupling between photons, which are particles of light that carry quantum information, and artificial atoms, units of matter that are often used to store information in a quantum computer.

Now, MIT researchers have demonstrated what they believe is the strongest nonlinear light-matter coupling ever achieved in a quantum system. Their experiment is a step toward realizing quantum operations and readout that could be performed in a few nanoseconds.

The researchers used a novel superconducting circuit architecture to show nonlinear light-matter coupling that is about an order of magnitude stronger than prior demonstrations, which could enable a quantum processor to run about 10 times faster.

There is still much work to be done before the architecture could be used in a real quantum computer, but demonstrating the fundamental physics behind the process is a major step in the right direction, says Yufeng “Bright” Ye SM ’20, PhD ’24, lead author of a paper on this research.

“This would really eliminate one of the bottlenecks in quantum computing. Usually, you have to measure the results of your computations in between rounds of error correction. This could accelerate how quickly we can reach the fault-tolerant quantum computing stage and be able to get real-world applications and value out of our quantum computers,” says Ye.

He is joined on the paper by senior author Kevin O’Brien, an associate professor and principal investigator in the Research Laboratory of Electronics at MIT who leads the Quantum Coherent Electronics Group in the Department of Electrical Engineering and Computer Science (EECS), as well as others at MIT, MIT Lincoln Laboratory, and Harvard University. The research appears today in Nature Communications.

A new coupler

This physical demonstration builds on years of theoretical research in the O’Brien group.

After Ye joined the lab as a PhD student in 2019, he began developing a specialized photon detector to enhance quantum information processing.

Through that work, he invented a new type of quantum coupler, which is a device that facilitates interactions between qubits. Qubits are the building blocks of a quantum computer. This so-called quarton coupler had so many potential applications in quantum operations and readout that it quickly became a focus of the lab.

This quarton coupler is a special type of superconducting circuit that has the potential to generate extremely strong nonlinear coupling, which is essential for running most quantum algorithms. As the researchers feed more current into the coupler, it creates an even stronger nonlinear interaction. In this sense, nonlinearity means a system behaves in a way that is greater than the sum of its parts, exhibiting more complex properties.

“Most of the useful interactions in quantum computing come from nonlinear coupling of light and matter. If you can get a more versatile range of different types of coupling, and increase the coupling strength, then you can essentially increase the processing speed of the quantum computer,” Ye explains.

For quantum readout, researchers shine microwave light onto a qubit and then, depending on whether that qubit is in state 0 or 1, there is a frequency shift on its associated readout resonator. They measure this shift to determine the qubit’s state.

Nonlinear light-matter coupling between the qubit and resonator enables this measurement process.

The MIT researchers designed an architecture with a quarton coupler connected to two superconducting qubits on a chip. They turn one qubit into a resonator and use the other qubit as an artificial atom which stores quantum information. This information is transferred in the form of microwave light particles called photons.

“The interaction between these superconducting artificial atoms and the microwave light that routes the signal is basically how an entire superconducting quantum computer is built,” Ye explains.

Enabling faster readout

The quarton coupler creates nonlinear light-matter coupling between the qubit and resonator that’s about an order of magnitude stronger than researchers had achieved before. This could enable a quantum system with lightning-fast readout.

“This work is not the end of the story. This is the fundamental physics demonstration, but there is work going on in the group now to realize really fast readout,” O’Brien says.

That would involve adding additional electronic components, such as filters, to produce a readout circuit that could be incorporated into a larger quantum system.

The researchers also demonstrated extremely strong matter-matter coupling, another type of qubit interaction that is important for quantum operations. This is another area they plan to explore with future work.

Fast operations and readout are especially important for quantum computers because qubits have finite lifespans, a concept known as coherence time.

Stronger nonlinear coupling enables a quantum processor to run faster and with lower error, so the qubits can perform more operations in the same amount of time. This means the qubits can run more rounds of error correction during their lifespans.

“The more runs of error correction you can get in, the lower the error will be in the results,” Ye says.

In the long run, this work could help scientists build a fault-tolerant quantum computer, which is essential for practical, large-scale quantum computation.

This research was supported, in part, by the Army Research Office, the AWS Center for Quantum Computing, and the MIT Center for Quantum Engineering.

Newly published results of a randomized, controlled clinical trial in Japan among more than 170 children aged 1 to 6 who underwent surgery show that by using electroencephalogram (EEG) readings of brain waves to monitor unconsciousness, an anesthesiologist can significantly reduce the amount of the anesthesia administered to safely induce and sustain each patient’s anesthetized state. On average, the little patients experienced significant improvements in several post-operative outcomes, including quicker recovery and reduced incidence of delirium.

“I think the main takeaway is that in kids, using the EEG, we can reduce the amount of anesthesia we give them and maintain the same level of unconsciousness,” says study co-author Emery N. Brown, the Edward Hood Taplin Professor of Medical Engineering and Computational Neuroscience at MIT, an anesthesiologist at Massachusetts General Hospital, and a professor at Harvard Medical School. The study appeared April 21 in JAMA Pediatrics.

Yasuko Nagasaka, chair of anesthesiology at Tokyo Women’s Medical University and a former colleague of Brown’s in the United States, designed the study. She asked Brown to train and advise lead author Kiyoyuki Miyasaka of St. Luke’s International Hospital in Tokyo on how to use EEG to monitor unconsciousness and adjust anesthesia dosing in children. Miyasaka then served as the anesthesiologist for all patients in the trial. Attending anesthesiologists not involved in the study were always on hand to supervise.

Brown’s research in The Picower Institute for Learning and Memory, the Institute for Medical Engineering and Science, and the Department of Brain and Cognitive Sciences at MIT has shown that a person’s level of consciousness under any particular anesthetic drug is discernible from patterns of their brain waves. Each child’s brain waves were measured with EEG, but in the control group Miyasaka adhered to standard anesthesia dosing protocols while in the experimental group he used the EEG measures as a guide for dosing. The results show that when he used EEG, he was able to induce the desired level of unconsciousness with a concentration of 2 percent sevoflurane gas, rather than the standard 5 percent. Maintenance of unconsciousness, meanwhile, only turned out to require 0.9 percent concentration, rather than the standard 2.5 percent.

Meanwhile, a separate researcher, blinded to whether EEG or standard protocols were used, assessed the kids for “pediatric anesthesia emergence delirium” (PAED), in which children sometimes wake up from anesthesia with a set of side effects including lack of eye contact, inconsolability, unawareness of surroundings, restlessness, and non-purposeful movements. Children who received standard anesthesia dosing met the threshold for PAED in 35 percent of cases (30 out of 86), while children who received EEG-guided dosing met the threshold in 21 percent of cases (19 out of 91). The difference of 14 percentage points was statistically significant.

Meanwhile, the authors reported that, on average, EEG-guided patients had breathing tubes removed 3.3 minutes earlier, emerged from anesthesia 21.4 minutes earlier, and were discharged from post-acute care 16.5 minutes earlier than patients who received anesthesia according to the standard protocol. All of these differences were statistically significant. Also, no child in the study ever became aware during surgery.

The authors noted that the quicker recovery among patients who received EEG-guided anesthesia was not only better medically, but also reduced health-care costs. Time in post-acute care in the United States costs about $46 a minute, so the average reduced time of 16.5 minutes would save about $750 per case. Sevoflurane is also a potent greenhouse gas, Brown notes, so reducing its use is better for the environment.

In the study, the authors also present comparisons of the EEG recordings from children in the control and experimental groups. There are notable differences in the “spectrograms” that charted the power of individual brain wave frequencies both as children were undergoing surgery and while they were approaching emergence from anesthesia, Brown says.

For instance, among children who received EEG-guided dosing, there are well-defined bands of high power at about 1-3 Hertz and 10-12 Hz. In children who received standard protocol dosing, the entire range of frequencies up to about 15 Hz are at high power. In another example, children who experienced PAED showed higher power at several frequencies up to 30Hz than children who did not experience PAED.

The findings further validate the idea that monitoring brain waves during surgery can provide anesthesiologists with actionable guidance to improve patient care, Brown says. Training in reading EEGs and guiding dosing can readily be integrated in the continuing medical education practices of hospitals, he adds.

In addition to Miyasuka, Brown, and Nagasaka, Yasuyuki Suzuki is a study co-author.

Funding sources for the study include the MIT-Massachusetts General Brigham Brain Arousal State Control Innovation Center, the Freedom Together Foundation, and the Picower Institute.

For more than 30 years, Course 7 (Biology) students have descended to the expansive, windowless basement of Building 68 to learn practical skills that are the centerpiece of undergraduate biology education at the Institute. The lines of benches and cabinets of supplies that make up the underground MIT Biology Teaching Lab could easily feel dark and isolated. 

In the corner of this room, however, sits Senior Technical Instructor Vanessa Cheung ’02, who manages to make the space seem sunny and communal.

“We joke that we could rig up a system of mirrors to get just enough daylight to bounce down from the stairwell,” Cheung says with a laugh. “It is a basement, but I am very lucky to have this teaching lab space. It is huge and has everything we need.”

This optimism and gratitude fostered by Cheung is critical, as MIT undergrad students enrolled in classes 7.002 (Fundamentals of Experimental Molecular Biology) and 7.003 (Applied Molecular Biology Laboratory) spend four-hour blocks in the lab each week, learning the foundations of laboratory technique and theory for biological research from Cheung and her colleagues.

Running toward science education

Cheung’s love for biology can be traced back to her high school cross country and track coach, who also served as her second-year biology teacher. The sport and the fundamental biological processes she was learning about in the classroom were, in fact, closely intertwined. 

“He told us about how things like ATP [adenosine triphosphate] and the energy cycle would affect our running,” she says. “Being able to see that connection really helped my interest in the subject.”

That inspiration carried her through a move from her hometown of Pittsburgh, Pennsylvania, to Cambridge, Massachusetts, to pursue an undergraduate degree at MIT, and through her thesis work to earn a PhD in genetics at Harvard Medical School. She didn’t leave running behind either: To this day, she can often be found on the Charles River Esplanade, training for her next marathon. 

She discovered her love of teaching during her PhD program. She enjoyed guiding students so much that she spent an extra semester as a teaching assistant, outside of the one required for her program. 

“I love research, but I also really love telling people about research,” Cheung says.

Cheung herself describes lab instruction as the “best of both worlds,” enabling her to pursue her love of teaching while spending every day at the bench, doing experiments. She emphasizes for students the importance of being able not just to do the hands-on technical lab work, but also to understand the theory behind it.

“The students can tend to get hung up on the physical doing of things — they are really concerned when their experiments don’t work,” she says. “We focus on teaching students how to think about being in a lab — how to design an experiment and how to analyze the data.”

Although her talent for teaching and passion for science led her to the role, Cheung doesn’t hesitate to identify the students as her favorite part of the job. 

“It sounds cheesy, but they really do keep the job very exciting,” she says.

Using mind and hand in the lab

Cheung is the type of person who lights up when describing how much she “loves working with yeast.” 

“I always tell the students that maybe no one cares about yeast except me and like three other people in the world, but it is a model organism that we can use to apply what we learn to humans,” Cheung explains.

Though mastering basic lab skills can make hands-on laboratory courses feel “a bit cookbook,” Cheung is able to get the students excited with her enthusiasm and clever curriculum design. 

“The students like things where they can get their own unique results, and things where they have a little bit of freedom to design their own experiments,” she says. So, the lab curriculum incorporates opportunities for students to do things like identify their own unique yeast mutants and design their own questions to test in a chemical engineering module.

Part of what makes theory as critical as technique is that new tools and discoveries are made frequently in biology, especially at MIT. For example, there has been a shift from a focus on RNAi to CRISPR as a popular lab technique in recent years, and Cheung muses that CRISPR itself may be overshadowed within only a few more years — keeping students learning at the cutting edge of biology is always on Cheung’s mind. 

“Vanessa is the heart, soul, and mind of the biology lab courses here at MIT, embodying ‘mens et manus’ [‘mind and hand’],” says technical lab instructor and Biology Teaching Lab Manager Anthony Fuccione. 

Support for all students

Cheung’s ability to mentor and guide students earned her a School of Science Dean’s Education and Advising Award in 2012, but her focus isn’t solely on MIT undergraduate students. 

In fact, according to Cheung, the earlier students can be exposed to science, the better. In addition to her regular duties, Cheung also designs curriculum and teaches in the LEAH Knox Scholars Program. The two-year program provides lab experience and mentorship for low-income Boston- and Cambridge-area high school students. 

Paloma Sanchez-Jauregui, outreach programs coordinator who works with Cheung on the program, says Cheung has a standout “growth mindset” that students really appreciate.

“Vanessa teaches students that challenges — like unexpected PCR results — are part of the learning process,” Sanchez-Jauregui says. “Students feel comfortable approaching her for help troubleshooting experiments or exploring new topics.”

Cheung’s colleagues report that they admire not only her talents, but also her focus on supporting those around her. Technical Instructor and colleague Eric Chu says Cheung “offers a lot of help to me and others, including those outside of the department, but does not expect reciprocity.”

Professor of biology and co-director of the Department of Biology undergraduate program Adam Martin says he “rarely has to worry about what is going on in the teaching lab.” According to Martin, Cheung is ”flexible, hard-working, dedicated, and resilient, all while being kind and supportive to our students. She is a joy to work with.” 

The ocean’s deep-sea bed is scattered with ancient rocks, each about the size of a closed fist, called “polymetallic nodules.” Elsewhere, along active and inactive hydrothermal vents and the deep ocean’s ridges, volcanic arcs, and tectonic plate boundaries, and on the flanks of seamounts, lie other types of mineral-rich deposits containing high-demand minerals.

The minerals found in the deep ocean are used to manufacture products like the lithium-ion batteries used to power electric vehicles, cell phones, or solar cells. In some cases, the estimated resources of critical mineral deposits in parts of the abyssal ocean exceed global land-based reserves severalfold.

“Society wants electric-powered vehicles, solar cells for clean energy, but all of this requires resources,” says Thomas Peacock, professor of mechanical engineering at MIT, in a video discussing his research. “Land-based resources are getting depleted, or are more challenging to access. In parts of the ocean, there are much more of these resources than in land-based reserve. The question is: Can it be less impactful to mine some of these resources from the ocean, rather than from land?”

Deep-sea mining is a new frontier in mineral extraction, with potentially significant implications for industry and the global economy, and important environmental and societal considerations. Through research, scientists like Peacock study the impacts of deep-sea mining activity objectively and rigorously, and can bring evidence to bear on decision-making. 

Mining activities, whether on land or at sea, can have significant impacts on the environment at local, regional, and global scales. As interest in deep-seabed mining is increasing, driven by the surging demand for critical minerals, scientific inquiries help illuminate the trade-offs.

Peacock has long studied the potential impacts of deep-sea mining in a region of the Pacific Ocean known as the Clarion Clipperton Zone (CCZ), where polymetallic nodules abound. A decade ago, his research group began studying deep-sea mining, seeing a critical need to develop monitoring and modeling capabilities for assessing the scale of impact.

Today, his MIT Environmental Dynamics Laboratory (ENDLab) is at the forefront of advancing understanding for emerging ocean utilization technologies. With research anchored in fundamental fluid dynamics, the team is developing cutting-edge monitoring programs, novel sensors, and modeling tools.

“We are studying the form of suspended sediment from deep sea mining operations, testing a new sensor for sediment and another new sensor for turbulence, studying the initial phases of the sediment plume development, and analyzing data from the 2021 and 2022 technology trials in the Pacific Ocean,” he explains.

In deep-sea nodule mining, vehicles collect nodules from the ocean floor and convey them back to a vessel above. After the critical materials are collected on the vessel, some leftover sediment may be returned to the deep-water column. The resulting sediment plumes, and their potential impacts, are a key focus of the team’s work.

A 2022 study conducted in the CCZ investigated the dynamics of sediment plumes near a deep-seabed polymetallic nodule mining vehicle. The experiments reveal most of the released sediment-laden water, between 92 and 98 percent, stayed close to the sea-bed floor, spreading laterally. The results suggest that turbidity current dynamics set the fraction of sediment that remains suspended in the water, along with the scale of the subsequent ambient sediment plume. The implications of the process, which had been previously overlooked, are substantial for plume modeling and informative for environmental impact statements.

“New model breakthroughs can help us make increasingly trustworthy predictions,” he says. The team also contributed to a recent study, published in the journal Nature, which showed that sediment deposited away from a test mining site gets cleared away, most likely by ocean currents, and reported on any observed biological recovery.

Researchers observed a site four decades after a nodule test mining experiment. Although biological impacts in many groups of organisms were present, populations of several organisms, including sediment macrofauna, mobile deposit feeders, and even large-sized sessile fauna, had begun to reestablish despite persistent physical changes at the seafloor. The study was led by the National Oceanography Centre in the U.K.

“A great deal has been learned about the fluid mechanics of deep-sea mining, in particular when it comes to deep-sea mining sediment plumes,” says Peacock, adding that the scientific progress continues with more results on the way. The work is setting new standards for in-situ monitoring of suspended sediment properties, and for how to interpret field data from recent technical trials.

Whether you are a person about town or a worm in a dish, life can throw all kinds of circumstances your way. What you need is a nervous system flexible enough to cope. In a new study, MIT neuroscientists show how even a simple animal can repurpose brain circuits and the chemical signals, or “neuromodulators,” in its brain to muster an adaptive response to an infection. The study therefore may provide a model for understanding how brains in more complex organisms, including ourselves, manage to use what they have to cope with shifting internal states. 

“Neuromodulators play pivotal roles in coupling changes in animals’ internal states to their behavior,” the scientists write in their paper, recently published in Nature Communications. “How combinations of neuromodulators released from different neuronal sources control the diverse internal states that animals exhibit remains an open question.”

When C. elegans worms fed on infectious Pseudomonas bacteria, they ate less and became more lethargic. When the researchers looked across the nervous system to see how that behavior happened, they discovered that the worm had completely revamped the roles of several of its 302 neurons and some of the peptides they secrete across the brain to modulate behavior. Systems that responded to stress in one case or satiety in another became reconfigured to cope with the infection.

“This is a question of, how do you adapt to your environment with the highest level of flexibility given the set of neurons and neuromodulators you have,” says postdoc Sreeparna Pradhan, co-lead author of the new study in Nature Communications. “How do you make the maximum set of options available to you?”

The research to find out took place in the lab of senior author Steve Flavell, an associate professor in The Picower Institute for Learning and Memory and the Department of Brain and Cognitive Sciences and an investigator of the Howard Hughes Medical Institute. Pradhan, who was supported by a fellowship from MIT’s K. Lisa Yang Brain-Body Center during the work, teamed up with former Flavell Lab graduate student Gurrein Madan to lead the research.

Pradhan says the team discovered several surprises in the course of the study, including that a neuropeptide called FLP-13 completely flipped its function in infected animals versus animals experiencing other forms of stress. Previous research had shown that when worms are stressed by heat, a neuron called ALA releases FLP-13 to cause the worms to go into quiescence, a sleep-like state. But when the worms in the new study ate Pseudomonas bacteria, a band of other neurons released FLP-13 to fight off quiescence, enabling the worms to survive longer. Meanwhile, ALA took on a completely different role during sickness: leading the charge to suppress feeding by emitting a different group of peptides.

A comprehensive approach

To understand how the worms responded to infection, the team tracked many features of the worms’ behavior for days and made genetic manipulations to probe the underlying mechanisms at play. They also recorded activity across the worms' whole brains. This kind of a comprehensive observation and experimentation is difficult to achieve in more complex animals, but C. elegans’ relative simplicity makes it a tractable testbed, Pradhan says. The team’s approach also is what allowed it to make so many unexpected findings.

For instance, Pradhan didn’t suspect that the ALA neuron would turn out to be the neuron that suppressed feeding, but when she observed their behavior for long enough, she started to realize the reduced feeding arose from the worms taking little breaks that they wouldn’t normally take. As she and Madan were manipulating more than a dozen genes they thought might be affecting behavior and feeding in the worm, she included another called ceh-17 that she had read about years ago that seemed to promote bouts of “microsleep” in the worms. When they knocked out ceh-17, they found that those worms didn’t reduce feeding when they got infected, unlike normal animals. It just so happens that ceh-17 is specifically needed for ALA to function properly, so that’s when the team realized ALA might be involved in the feeding-reduction behavior.

To know for sure, they then knocked out the various peptides that ALA releases and saw that when they knocked out three in particular, flp-24, nlp-8 and flp-7, infected worms didn’t exhibit reduced feeding upon infection. That clinched that ALA drives the reduced feeding behavior by emitting those three peptides.

Meanwhile, Pradhan and Madan’s screens also revealed that when infected worms were missing flp-13, they would go into a quiescence state much sooner than infected worms with the peptide available. Notably, the worms that fought off the quiescence state lived longer. They found that fighting off quiescence depended on the FLP-13 coming from four neurons (I5, I1, ASH and OLL), but not from ALA. Further experiments showed that FLP-13 acted on a widespread neuropeptide receptor called DMSR-1 to prevent quiescence.

Having a little nap

The last major surprise of the study was that the quiescence that Pseudomonas infection induces in worms is not the same as other forms of sleepiness that show up in other contexts, such as after satiety or heat stress. In those cases, worms don’t wake easily (with a little poke), but amid infection their quiescence was readily reversible. It seemed more like lethargy than sleep. Using the lab’s ability image all neural activity during behavior, Pradhan and Madan discerned that a neuron called ASI was particularly active during the bouts of lethargy. That observation solidified further when they showed that ASI’s secretion of the peptide DAF-7 was required for the quiescence to emerge in infected animals.

In all, the study showed that the worms repurpose and reconfigure — sometimes to the point of completely reversing — the functions of neurons and peptides to mount an adaptive response to infection, versus a different problem like stress. The results therefore shed light on what has been a tricky question to resolve. How do brains use their repertoire of cells, circuits, and neuromodulators to deal with what life hands them? At least part of the answer seems to be by reshuffling existing components, rather than creating unique ones for each situation.

“The states of stress, satiety, and infection are not induced by unique sets of neuromodulators," the authors wrote in their paper. "Instead, one larger set of neuromodulators may be deployed from different sources and in different combinations to specify these different internal states.”

In addition to Pradhan, Madan, and Flavell, the paper’s other authors are Di Kang, Eric Bueno, Adam Atanas, Talya Kramer, Ugur Dag, Jessica Lage, Matthew Gomes, Alicia Kun-Yang Lu, and Jungyeon Park.

Support for the research came from the the Picower Institute, the Freedom Together Foundation, the K. Lisa Yang Brain-Body Center, and the Yang Tan Collective at MIT; the National Institutes of Health; the McKnight Foundation; the Alfred P. Sloan Foundation; and the Howard Hughes Medical Institute.

When farmers apply pesticides to their crops, 30 to 50 percent of the chemicals end up in the air or soil instead of on the plants. Now, a team of researchers from MIT and Singapore has developed a much more precise way to deliver substances to plants: tiny needles made of silk.

In a study published today in Nature Nanotechnology, the researchers developed a way to produce large amounts of these hollow silk microneedles. They used them to inject agrochemicals and nutrients into plants, and to monitor their health.

“There’s a big need to make agriculture more efficient,” says Benedetto Marelli, the study’s senior author and an associate professor of civil and environmental engineering at MIT. “Agrochemicals are important for supporting our food system, but they’re also expensive and bring environmental side effects, so there’s a big need to deliver them precisely.”

Yunteng Cao PhD ’22, currently a postdoc Yale University, and Doyoon Kim, a former postdoc in the Marelli lab, led the study, which included a collaboration with the Disruptive and Sustainable Technologies for Agricultural Precision (DiSTAP) interdisciplinary research group at the Singapore-MIT Alliance for Research and Technology (SMART).

In demonstrations, the team used the technique to give plants iron to treat a disease known as chlorosis, and to add vitamin B12 to tomato plants to make them more nutritious. The researchers also showed the microneedles could be used to monitor the quality of fluids flowing into plants and to detect when the surrounding soil contained heavy metals.

Overall, the researchers believe the microneedles could serve as a new kind of plant interface for real-time health monitoring and biofortification.

“These microneedles could be a tool for plant scientists so they can understand more about plant health and how they grow,” Marelli says. “But they can also be used to add value to crops, making them more resilient and possibly even increasing yields.”

The inner workings of plants

Accessing the inner tissues of living plants requires scientists to get through the plants’ waxy skin without causing too much stress. In previous work, the researchers used silk-based microneedles to deliver agrochemicals to plants in lab environments and to detect pH changes in living plants. But these initial efforts involved small payloads, limiting their applications in commercial agriculture.

“Microneedles were originally developed for the delivery of vaccines or other drugs in humans,” Marelli explains. “Now we’ve adapted it so that the technology can work with plants, but initially we could not deliver sufficient doses of agrochemicals and nutrients to mitigate stressors or enhance crop nutritional values.”

Hollow structures could increase the amount of chemicals microneedles can deliver, but Marelli says creating those structures at scale has historically required clean rooms and expensive facilities like the ones found inside the MIT.nano building.

For this study, Cao and Kim created a new way to manufacture hollow silk microneedles by combining silk fibroin protein with a salty solution inside tiny, cone-shaped molds. As water evaporated from the solution, the silk solidified into the mold while the salt forms crystalline structures inside the molds. When the salt was removed, it left behind in each needle a hollow structure or tiny pores, depending on the salt concentration and the separation of the organic and inorganic phases.

“It’s a pretty simple fabrication process. It can be done outside of a clean room — you could do it in your kitchen if you wanted,” Kim says. “It doesn’t require any expensive machinery.”

The researchers then tested their microneedles’ ability to deliver iron to iron-deficient tomato plants, which can cause a disease known as chlorosis. Chlorosis can decrease yields, but treating it by spraying crops is inefficient and can have environmental side effects. The researchers showed that their hollow microneedles could be used for the sustained delivery of iron without harming the plants.

The researchers also showed their microneedles could be used to fortify crops while they grow. Historically, crop fortification efforts have focused on minerals like zinc or iron, with vitamins only added after the food is harvested.

In each case, the researchers applied the microneedles to the stalks of plants by hand, but Marelli envisions equipping autonomous vehicles and other equipment already used in farms to automate and scale the process.

As part of the study, the researchers used microneedles to deliver vitamin B12, which is primarily found naturally in animal products, into the stalks of growing tomatoes, showing that vitamin B12 moved into the tomato fruits before harvest. The researchers propose their method could be used to fortify more plants with the vitamin.

Co-author Daisuke Urano, a plant scientist with DiSTAP, explains that “through a comprehensive assessment, we showed minimal adverse effects from microneedle injections in plants, with no observed short- or long-term negative impacts.”

“This new delivery mechanism opens up a lot of potential applications, so we wanted to do something nobody had done before,” Marelli explains.

Finally, the researchers explored the use of their microneedles to monitor the health of plants by studying tomatoes growing in hydroponic solutions contaminated with cadmium, a toxic metal commonly found in farms close to industrial and mining sites. They showed their microneedles absorbed the toxin within 15 minutes of being injected into the tomato stalks, offering a path to rapid detection.

Current advanced techniques for monitoring plant health, such as colorimetric and hyperspectral lead analyses, can only detect problems after plants growth is already being stunted. Other methods, such as sap sampling, can be too time-consuming.

Microneedles, in contrast, could be used to more easily collect sap for ongoing chemical analysis. For instance, the researchers showed they could monitor cadmium levels in tomatoes over the course of 18 hours.

A new platform for farming

The researchers believe the microneedles could be used to complement existing agricultural practices like spraying. The researchers also note the technology has applications beyond agriculture, such as in biomedical engineering.

“This new polymeric microneedle fabrication technique may also benefit research in microneedle-mediated transdermal and intradermal drug delivery and health monitoring,” Cao says.

For now, though, Marelli believes the microneedles offer a path to more precise, sustainable agriculture practices.

“We want to maximize the growth of plants without negatively affecting the health of the farm or the biodiversity of surrounding ecosystems,” Marelli says. “There shouldn’t be a trade-off between the agriculture industry and the environment. They should work together.”

This work was supported, in part, by the U.S. Office of Naval Research, the U.S. National Science Foundation, SMART, the National Research Foundation of Singapore, and the Singapore Prime Minister’s Office.