Epigenomic analysis sheds light on risk factors for ALS

For most patients, it’s unknown exactly what causes amyotrophic lateral sclerosis (ALS), a disease characterized by degeneration of motor neurons that impairs muscle control and eventually leads to death.

Studies have identified certain genes that confer a higher risk of the disease, but scientists believe there are many more genetic risk factors that have yet to be discovered. One reason why these drivers have been hard to find is that some are found in very few patients, making it hard to pick them out without a very large sample of patients. Additionally, some of the risk may be driven by epigenomic factors, rather than mutations in protein-coding genes.

Working with the Answer ALS consortium, a team of MIT researchers has analyzed epigenetic modifications — tags that determine which genes are turned on in a cell — in motor neurons derived from induced pluripotent stem (IPS) cells from 380 ALS patients.

This analysis revealed a strong differential signal associated with a known subtype of ALS, and about 30 locations with modifications that appear to be linked to rates of disease progression in ALS patients. The findings may help scientists develop new treatments that are targeted to patients with certain genetic risk factors.

“If the root causes are different for all these different versions of the disease, the drugs will be very different and the signals in IPS cells will be very different,” says Ernest Fraenkel, the Grover M. Hermann Professor in Health Sciences and Technology in MIT’s Department of Biological Engineering and the senior author of the study. “We may get to a point in a decade or so where we don’t even think of ALS as one disease, where there are drugs that are treating specific types of ALS that only work for one group of patients and not for another.”

MIT postdoc Stanislav Tsitkov is the lead author of the paper, which appears today in Nature Communications.

Finding risk factors

ALS is a rare disease that is estimated to affect about 30,000 people in the United States. One of the challenges in studying the disease is that while genetic variants are believed to account for about 50 percent of ALS risk (with environmental factors making up the rest), most of the variants that contribute to that risk have not been identified.

Similar to Alzheimer’s disease, there may be a large number of genetic variants that can confer risk, but each individual patient may carry only a small number of those. This makes it difficult to identify the risk factors unless scientists have a very large population of patients to analyze.

“Because we expect the disease to be heterogeneous, you need to have large numbers of patients before you can pick up on signals like this. To really be able to classify the subtypes of disease, we’re going to need to look at a lot of people,” Fraenkel says.

About 10 years ago, the Answer ALS consortium began to collect large numbers of patient samples, which could allow for larger-scale studies that might reveal some of the genetic drivers of the disease. From blood samples, researchers can create induced pluripotent stem cells and then induce them to differentiate into motor neurons, the cells most affected by ALS.

“We don’t think all ALS patients are going to be the same, just like all cancers are not the same. And the goal is being able to find drivers of the disease that could be therapeutic targets,” Fraenkel says.

In this study, Fraenkel and his colleagues wanted to see if patient-derived cells could offer any information about molecular differences that are relevant to ALS. They focused on epigenomic modifications, using a method called ATAC-seq to measure chromatin density across the genome of each cell. Chromatin is a complex of DNA and proteins that determines which genes are accessible to be transcribed by the cell, depending on how densely packed the chromatin is.

In data that were collected and analyzed over several years, the researchers did not find any global signal that clearly differentiated the 380 ALS patients in their study from 80 healthy control subjects. However, they did find a strong differential signal associated with a subtype of ALS, characterized by a genetic mutation in the C9orf72 gene.

Additionally, they identified about 30 regions that were associated with slower rates of disease progression in ALS patients. Many of these regions are located near genes related to the cellular inflammatory response; interestingly, several of the identified genes have also been implicated in other neurodegenerative diseases, such as Parkinson’s disease.

“You can use a small number of these epigenomic regions and look at the intensity of the signal there, and predict how quickly someone’s disease will progress. That really validates the hypothesis that the epigenomics can be used as a filter to better understand the contribution of the person’s genome,” Fraenkel says.

“By harnessing the very large number of participant samples and extensive data collected by the Answer ALS Consortium, these studies were able to rigorously test whether the observed changes might be artifacts related to the techniques of sample collection, storage, processing, and analysis, or truly reflective of important biology,” says Lyle Ostrow, an associate professor of neurology at the Lewis Katz School of Medicine at Temple University, who was not involved in the study. “They developed standard ways to control for these variables, to make sure the results can be accurately compared. Such studies are incredibly important for accelerating ALS therapy development, as they will enable data and samples collected from different studies to be analyzed together.”

Targeted drugs

The researchers now hope to further investigate these genomic regions and see how they might drive different aspects of ALS progression in different subsets of patients. This could help scientists develop drugs that might work in different groups of patients, and help them identify which patients should be chosen for clinical trials of those drugs, based on genetic or epigenetic markers.

Last year, the U.S. Food and Drug Administration approved a drug called tofersen, which can be used in ALS patients with a mutation in a gene called SOD1. This drug is very effective for those patients, who make up about 1 percent of the total population of people with ALS. Fraenkel’s hope is that more drugs can be developed for, and tested in, people with other genetic drivers of ALS.

“If you had a drug like tofersen that works for 1 percent of patients and you just gave it to a typical phase two clinical trial, you probably wouldn’t have anybody with that mutation in the trial, and it would’ve failed. And so that drug, which is a lifesaver for people, would never have gotten through,” Fraenkel says.

The MIT team is now using an approach called quantitative trait locus (QTL) analysis to try to identify subgroups of ALS patients whose disease is driven by specific genomic variants.

“We can integrate the genomics, the transcriptomics, and the epigenomics, as a way to find subgroups of ALS patients who have distinct phenotypic signatures from other ALS patients and healthy controls,” Tsitkov says. “We have already found a few potential hits in that direction.”

The research was funded by the Answer ALS program, which is supported by the Robert Packard Center for ALS Research at Johns Hopkins University, Travelers Insurance, ALS Finding a Cure Foundation, Stay Strong Vs. ALS, Answer ALS Foundation, Microsoft, Caterpillar Foundation, American Airlines, Team Gleason, the U.S. National Institutes of Health, Fishman Family Foundation, Aviators Against ALS, AbbVie Foundation, Chan Zuckerberg Initiative, ALS Association, National Football League, F. Prime, M. Armstrong, Bruce Edwards Foundation, the Judith and Jean Pape Adams Charitable Foundation, Muscular Dystrophy Association, Les Turner ALS Foundation, PGA Tour, Gates Ventures, and Bari Lipp Foundation. This work was also supported, in part, by grants from the National Institutes of Health and the MIT-GSK Gertrude B. Elion Research Fellowship Program for Drug Discovery and Disease.

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Fostering research, careers, and community in materials science

Gabrielle Wood, a junior at Howard University majoring in chemical engineering, is on a mission to improve the sustainability and life cycles of natural resources and materials. Her work in the Materials Initiative for Comprehensive Research Opportunity (MICRO) program has given her hands-on experience with many different aspects of research, including MATLAB programming, experimental design, data analysis, figure-making, and scientific writing.

Wood is also one of 10 undergraduates from 10 universities around the United States to participate in the first MICRO Summit earlier this year. The internship program, developed by the MIT Department of Materials Science and Engineering (DMSE), first launched in fall 2021. Now in its third year, the program continues to grow, providing even more opportunities for non-MIT undergraduate students — including the MICRO Summit and the program’s expansion to include Northwestern University.

“I think one of the most valuable aspects of the MICRO program is the ability to do research long term with an experienced professor in materials science and engineering,” says Wood. “My school has limited opportunities for undergraduate research in sustainable polymers, so the MICRO program allowed me to gain valuable experience in this field, which I would not otherwise have.”

Like Wood, Griheydi Garcia, a senior chemistry major at Manhattan College, values the exposure to materials science, especially since she is not able to learn as much about it at her home institution.

“I learned a lot about crystallography and defects in materials through the MICRO curriculum, especially through videos,” says Garcia. “The research itself is very valuable, as well, because we get to apply what we’ve learned through the videos in the research we do remotely.”

Expanding research opportunities

From the beginning, the MICRO program was designed as a fully remote, rigorous education and mentoring program targeted toward students from underserved backgrounds interested in pursuing graduate school in materials science or related fields. Interns are matched with faculty to work on their specific research interests.

Jessica Sandland ’99, PhD ’05, principal lecturer in DMSE and co-founder of MICRO, says that research projects for the interns are designed to be work that they can do remotely, such as developing a machine-learning algorithm or a data analysis approach.

“It’s important to note that it’s not just about what the program and faculty are bringing to the student interns,” says Sandland, a member of the MIT Digital Learning Lab, a joint program between MIT Open Learning and the Institute’s academic departments. “The students are doing real research and work, and creating things of real value. It’s very much an exchange.”

Cécile Chazot PhD ’22, now an assistant professor of materials science and engineering at Northwestern University, had helped to establish MICRO at MIT from the very beginning. Once at Northwestern, she quickly realized that expanding MICRO to Northwestern would offer even more research opportunities to interns than by relying on MIT alone — leveraging the university’s strong materials science and engineering department, as well as offering resources for biomaterials research through Northwestern’s medical school. The program received funding from 3M and officially launched at Northwestern in fall 2023. Approximately half of the MICRO interns are now in the program with MIT and half are with Northwestern. Wood and Garcia both participate in the program via Northwestern.

“By expanding to another school, we’ve been able to have interns work with a much broader range of research projects,” says Chazot. “It has become easier for us to place students with faculty and research that match their interests.”

Building community

The MICRO program received a Higher Education Innovation grant from the Abdul Latif Jameel World Education Lab, part of MIT Open Learning, to develop an in-person summit. In January 2024, interns visited MIT for three days of presentations, workshops, and campus tours — including a tour of the MIT.nano building — as well as various community-building activities.

“A big part of MICRO is the community,” says Chazot. “A highlight of the summit was just seeing the students come together.”

The summit also included panel discussions that allowed interns to gain insights and advice from graduate students and professionals. The graduate panel discussion included MIT graduate students Sam Figueroa (mechanical engineering), Isabella Caruso (DMSE), and Eliana Feygin (DMSE). The career panel was led by Chazot and included Jatin Patil PhD ’23, head of product at SiTration; Maureen Reitman ’90, ScD ’93, group vice president and principal engineer at Exponent; Lucas Caretta PhD ’19, assistant professor of engineering at Brown University; Raquel D’Oyen ’90, who holds a PhD from Northwestern University and is a senior engineer at Raytheon; and Ashley Kaiser MS ’19, PhD ’21, senior process engineer at 6K.

Students also had an opportunity to share their work with each other through research presentations. Their presentations covered a wide range of topics, including: developing a computer program to calculate solubility parameters for polymers used in textile manufacturing; performing a life-cycle analysis of a photonic chip and evaluating its environmental impact in comparison to a standard silicon microchip; and applying machine learning algorithms to scanning transmission electron microscopy images of CrSBr, a two-dimensional magnetic material. 

“The summit was wonderful and the best academic experience I have had as a first-year college student,” says MICRO intern Gabriella La Cour, who is pursuing a major in chemistry and dual degree biomedical engineering at Spelman College and participates in MICRO through MIT. “I got to meet so many students who were all in grades above me … and I learned a little about how to navigate college as an upperclassman.” 

“I actually have an extremely close friendship with one of the students, and we keep in touch regularly,” adds La Cour. “Professor Chazot gave valuable advice about applications and recommendation letters that will be useful when I apply to REUs [Research Experiences for Undergraduates] and graduate schools.”

Looking to the future, MICRO organizers hope to continue to grow the program’s reach.

“We would love to see other schools taking on this model,” says Sandland. “There are a lot of opportunities out there. The more departments, research groups, and mentors that get involved with this program, the more impact it can have.”

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Natural language boosts LLM performance in coding, planning, and robotics

Large language models (LLMs) are becoming increasingly useful for programming and robotics tasks, but for more complicated reasoning problems, the gap between these systems and humans looms large. Without the ability to learn new concepts like humans do, these systems fail to form good abstractions — essentially, high-level representations of complex concepts that skip less-important details — and thus sputter when asked to do more sophisticated tasks.

Luckily, MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers have found a treasure trove of abstractions within natural language. In three papers to be presented at the International Conference on Learning Representations this month, the group shows how our everyday words are a rich source of context for language models, helping them build better overarching representations for code synthesis, AI planning, and robotic navigation and manipulation.

The three separate frameworks build libraries of abstractions for their given task: LILO (library induction from language observations) can synthesize, compress, and document code; Ada (action domain acquisition) explores sequential decision-making for artificial intelligence agents; and LGA (language-guided abstraction) helps robots better understand their environments to develop more feasible plans. Each system is a neurosymbolic method, a type of AI that blends human-like neural networks and program-like logical components.

LILO: A neurosymbolic framework that codes

Large language models can be used to quickly write solutions to small-scale coding tasks, but cannot yet architect entire software libraries like the ones written by human software engineers. To take their software development capabilities further, AI models need to refactor (cut down and combine) code into libraries of succinct, readable, and reusable programs.

Refactoring tools like the previously developed MIT-led Stitch algorithm can automatically identify abstractions, so, in a nod to the Disney movie “Lilo & Stitch,” CSAIL researchers combined these algorithmic refactoring approaches with LLMs. Their neurosymbolic method LILO uses a standard LLM to write code, then pairs it with Stitch to find abstractions that are comprehensively documented in a library.

LILO’s unique emphasis on natural language allows the system to do tasks that require human-like commonsense knowledge, such as identifying and removing all vowels from a string of code and drawing a snowflake. In both cases, the CSAIL system outperformed standalone LLMs, as well as a previous library learning algorithm from MIT called DreamCoder, indicating its ability to build a deeper understanding of the words within prompts. These encouraging results point to how LILO could assist with things like writing programs to manipulate documents like Excel spreadsheets, helping AI answer questions about visuals, and drawing 2D graphics.

“Language models prefer to work with functions that are named in natural language,” says Gabe Grand SM '23, an MIT PhD student in electrical engineering and computer science, CSAIL affiliate, and lead author on the research. “Our work creates more straightforward abstractions for language models and assigns natural language names and documentation to each one, leading to more interpretable code for programmers and improved system performance.”

When prompted on a programming task, LILO first uses an LLM to quickly propose solutions based on data it was trained on, and then the system slowly searches more exhaustively for outside solutions. Next, Stitch efficiently identifies common structures within the code and pulls out useful abstractions. These are then automatically named and documented by LILO, resulting in simplified programs that can be used by the system to solve more complex tasks.

The MIT framework writes programs in domain-specific programming languages, like Logo, a language developed at MIT in the 1970s to teach children about programming. Scaling up automated refactoring algorithms to handle more general programming languages like Python will be a focus for future research. Still, their work represents a step forward for how language models can facilitate increasingly elaborate coding activities.

Ada: Natural language guides AI task planning

Just like in programming, AI models that automate multi-step tasks in households and command-based video games lack abstractions. Imagine you’re cooking breakfast and ask your roommate to bring a hot egg to the table — they’ll intuitively abstract their background knowledge about cooking in your kitchen into a sequence of actions. In contrast, an LLM trained on similar information will still struggle to reason about what they need to build a flexible plan.

Named after the famed mathematician Ada Lovelace, who many consider the world’s first programmer, the CSAIL-led “Ada” framework makes headway on this issue by developing libraries of useful plans for virtual kitchen chores and gaming. The method trains on potential tasks and their natural language descriptions, then a language model proposes action abstractions from this dataset. A human operator scores and filters the best plans into a library, so that the best possible actions can be implemented into hierarchical plans for different tasks.

“Traditionally, large language models have struggled with more complex tasks because of problems like reasoning about abstractions,” says Ada lead researcher Lio Wong, an MIT graduate student in brain and cognitive sciences, CSAIL affiliate, and LILO coauthor. “But we can combine the tools that software engineers and roboticists use with LLMs to solve hard problems, such as decision-making in virtual environments.”

When the researchers incorporated the widely-used large language model GPT-4 into Ada, the system completed more tasks in a kitchen simulator and Mini Minecraft than the AI decision-making baseline “Code as Policies.” Ada used the background information hidden within natural language to understand how to place chilled wine in a cabinet and craft a bed. The results indicated a staggering 59 and 89 percent task accuracy improvement, respectively.

With this success, the researchers hope to generalize their work to real-world homes, with the hopes that Ada could assist with other household tasks and aid multiple robots in a kitchen. For now, its key limitation is that it uses a generic LLM, so the CSAIL team wants to apply a more powerful, fine-tuned language model that could assist with more extensive planning. Wong and her colleagues are also considering combining Ada with a robotic manipulation framework fresh out of CSAIL: LGA (language-guided abstraction).

Language-guided abstraction: Representations for robotic tasks

Andi Peng SM ’23, an MIT graduate student in electrical engineering and computer science and CSAIL affiliate, and her coauthors designed a method to help machines interpret their surroundings more like humans, cutting out unnecessary details in a complex environment like a factory or kitchen. Just like LILO and Ada, LGA has a novel focus on how natural language leads us to those better abstractions.

In these more unstructured environments, a robot will need some common sense about what it’s tasked with, even with basic training beforehand. Ask a robot to hand you a bowl, for instance, and the machine will need a general understanding of which features are important within its surroundings. From there, it can reason about how to give you the item you want. 

In LGA’s case, humans first provide a pre-trained language model with a general task description using natural language, like “bring me my hat.” Then, the model translates this information into abstractions about the essential elements needed to perform this task. Finally, an imitation policy trained on a few demonstrations can implement these abstractions to guide a robot to grab the desired item.

Previous work required a person to take extensive notes on different manipulation tasks to pre-train a robot, which can be expensive. Remarkably, LGA guides language models to produce abstractions similar to those of a human annotator, but in less time. To illustrate this, LGA developed robotic policies to help Boston Dynamics’ Spot quadruped pick up fruits and throw drinks in a recycling bin. These experiments show how the MIT-developed method can scan the world and develop effective plans in unstructured environments, potentially guiding autonomous vehicles on the road and robots working in factories and kitchens.

“In robotics, a truth we often disregard is how much we need to refine our data to make a robot useful in the real world,” says Peng. “Beyond simply memorizing what’s in an image for training robots to perform tasks, we wanted to leverage computer vision and captioning models in conjunction with language. By producing text captions from what a robot sees, we show that language models can essentially build important world knowledge for a robot.”

The challenge for LGA is that some behaviors can’t be explained in language, making certain tasks underspecified. To expand how they represent features in an environment, Peng and her colleagues are considering incorporating multimodal visualization interfaces into their work. In the meantime, LGA provides a way for robots to gain a better feel for their surroundings when giving humans a helping hand. 

An “exciting frontier” in AI

“Library learning represents one of the most exciting frontiers in artificial intelligence, offering a path towards discovering and reasoning over compositional abstractions,” says assistant professor at the University of Wisconsin-Madison Robert Hawkins, who was not involved with the papers. Hawkins notes that previous techniques exploring this subject have been “too computationally expensive to use at scale” and have an issue with the lambdas, or keywords used to describe new functions in many languages, that they generate. “They tend to produce opaque 'lambda salads,' big piles of hard-to-interpret functions. These recent papers demonstrate a compelling way forward by placing large language models in an interactive loop with symbolic search, compression, and planning algorithms. This work enables the rapid acquisition of more interpretable and adaptive libraries for the task at hand.”

By building libraries of high-quality code abstractions using natural language, the three neurosymbolic methods make it easier for language models to tackle more elaborate problems and environments in the future. This deeper understanding of the precise keywords within a prompt presents a path forward in developing more human-like AI models.

MIT CSAIL members are senior authors for each paper: Joshua Tenenbaum, a professor of brain and cognitive sciences, for both LILO and Ada; Julie Shah, head of the Department of Aeronautics and Astronautics, for LGA; and Jacob Andreas, associate professor of electrical engineering and computer science, for all three. The additional MIT authors are all PhD students: Maddy Bowers and Theo X. Olausson for LILO, Jiayuan Mao and Pratyusha Sharma for Ada, and Belinda Z. Li for LGA. Muxin Liu of Harvey Mudd College was a coauthor on LILO; Zachary Siegel of Princeton University, Jaihai Feng of the University of California at Berkeley, and Noa Korneev of Microsoft were coauthors on Ada; and Ilia Sucholutsky, Theodore R. Sumers, and Thomas L. Griffiths of Princeton were coauthors on LGA. 

LILO and Ada were supported, in part, by ​​MIT Quest for Intelligence, the MIT-IBM Watson AI Lab, Intel, U.S. Air Force Office of Scientific Research, the U.S. Defense Advanced Research Projects Agency, and the U.S. Office of Naval Research, with the latter project also receiving funding from the Center for Brains, Minds and Machines. LGA received funding from the U.S. National Science Foundation, Open Philanthropy, the Natural Sciences and Engineering Research Council of Canada, and the U.S. Department of Defense.

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Nuno Loureiro named director of MIT’s Plasma Science and Fusion Center

Nuno Loureiro, professor of nuclear science and engineering and of physics, has been appointed the new director of the MIT Plasma Science and Fusion Center, effective May 1.

Loureiro is taking the helm of one of MIT’s largest labs: more than 250 full-time researchers, staff members, and students work and study in seven buildings with 250,000 square feet of lab space. A theoretical physicist and fusion scientist, Loureiro joined MIT as a faculty member in 2016, and was appointed deputy director of the Plasma Science and Fusion Center (PSFC) in 2022. Loureiro succeeds Dennis Whyte, who stepped down at the end of 2023 to return to teaching and research.

Stepping into his new role as director, Loureiro says, “The PSFC has an impressive tradition of discovery and leadership in plasma and fusion science and engineering. Becoming director of the PSFC is an incredible opportunity to shape the future of these fields. We have a world-class team, and it’s an honor to be chosen as its leader.”

Loureiro’s own research ranges widely. He is recognized for advancing the understanding of multiple aspects of plasma behavior, particularly turbulence and the physics underpinning solar flares and other astronomical phenomena. In the fusion domain, his work enables the design of fusion devices that can more efficiently control and harness the energy of fusing plasmas, bringing the dream of clean, near-limitless fusion power that much closer. 

Plasma physics is foundational to advancing fusion science, a fact Loureiro has embraced and that is relevant as he considers the direction of the PSFC’s multidisciplinary research. “But plasma physics is only one aspect of our focus. Building a scientific agenda that continues and expands on the PSFC’s history of innovation in all aspects of fusion science and engineering is vital, and a key facet of that work is facilitating our researchers’ efforts to produce the breakthroughs that are necessary for the realization of fusion energy.”

As the climate crisis accelerates, fusion power continues to grow in appeal: It produces no carbon emissions, its fuel is plentiful, and dangerous “meltdowns” are impossible. The sooner that fusion power is commercially available, the greater impact it can have on reducing greenhouse gas emissions and meeting global climate goals. While technical challenges remain, “the PSFC is well poised to meet them, and continue to show leadership. We are a mission-driven lab, and our students and staff are incredibly motivated,” Loureiro comments.

“As MIT continues to lead the way toward the delivery of clean fusion power onto the grid, I have no doubt that Nuno is the right person to step into this key position at this critical time,” says Maria T. Zuber, MIT’s presidential advisor for science and technology policy. “I look forward to the steady advance of plasma physics and fusion science at MIT under Nuno’s leadership.”

Over the last decade, there have been massive leaps forward in the field of fusion energy, driven in part by innovations like high-temperature superconducting magnets developed at the PSFC. Further progress is guaranteed: Loureiro believes that “The next few years are certain to be an exciting time for us, and for fusion as a whole. It’s the dawn of a new era with burning plasma experiments” — a reference to the collaboration between the PSFC and Commonwealth Fusion Systems, a startup company spun out of the PSFC, to build SPARC, a fusion device that is slated to turn on in 2026 and produce a burning plasma that yields more energy than it consumes. “It’s going to be a watershed moment,” says Loureiro.

He continues, “In addition, we have strong connections to inertial confinement fusion experiments, including those at Lawrence Livermore National Lab, and we’re looking forward to expanding our research into stellarators, which are another kind of magnetic fusion device.” Over recent years, the PSFC has significantly increased its collaboration with industrial partners such Eni, IBM, and others. Loureiro sees great value in this: “These collaborations are mutually beneficial: they allow us to grow our research portfolio while advancing companies’ R&D efforts. It’s very dynamic and exciting.”

Loureiro’s directorship begins as the PSFC is launching key tech development projects like LIBRA, a “blanket” of molten salt that can be wrapped around fusion vessels and perform double duty as a neutron energy absorber and a breeder for tritium (the fuel for fusion). Researchers at the PSFC have also developed a way to rapidly test the durability of materials being considered for use in a fusion power plant environment, and are now creating an experiment that will utilize a powerful particle accelerator called a gyrotron to irradiate candidate materials.

Interest in fusion is at an all-time high; the demand for researchers and engineers, particularly in the nascent commercial fusion industry, is reflected by the record number of graduate students that are studying at the PSFC — more than 90 across seven affiliated MIT departments. The PSFC’s classrooms are full, and Loureiro notes a palpable sense of excitement. “Students are our greatest strength,” says Loureiro. “They come here to do world-class research but also to grow as individuals, and I want to give them a great place to do that. Supporting those experiences, making sure they can be as successful as possible is one of my top priorities.” Loureiro plans to continue teaching and advising students after his appointment begins.

MIT President Sally Kornbluth’s recently announced Climate Project is a clarion call for Loureiro: “It’s not hyperbole to say MIT is where you go to find solutions to humanity’s biggest problems,” he says. “Fusion is a hard problem, but it can be solved with resolve and ingenuity — characteristics that define MIT. Fusion energy will change the course of human history. It’s both humbling and exciting to be leading a research center that will play a key role in enabling that change.” 

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Studies in empathy and analytics

Upon the advice of one of his soccer teammates, James Simon enrolled in 14.73 (The Challenge of World Poverty) as a first-year student to fulfill a humanities requirement. He went from knowing nothing about economics to learning about the subject from Nobel laureates.

The lessons created by professors Esther Duflo and Abhijit Banerjee revealed to Simon an entirely new way to use science to help humanity. One of the projects Simon learned about in this class assessed an area of India with a low vaccination rate and created a randomized, controlled trial to figure out the best way to fix this problem.

“What was really cool about the class was that it talked about huge problems in the world, like poverty, hunger, and lack of vaccinations, and it talked about how you could break them down using experiments and quantify the best way to solve them,” he says.

Galvanized by this experience, Simon joined a research project in the economics department and committed to a blended major in computer science, economics, and data. He began working on a research project with Senior Lecturer Sara Ellison in 2021 and has since contributed to multiple research papers published by the group, many concerning developmental economic issues. One of his most memorable projects explored the question of whether internet access helps bridge the gap between poor and wealthy countries. Simon collected data, conducted interviews, and did statistical analysis to develop answers to the group’s questions. Their paper was published in Competition Policy International in 2021.

Further bridging his economics studies with real-world efforts, Simon has become involved with the Guatemalan charity Project Somos, which is dedicated to challenging poverty through access to food and education. Through MIT’s Global Research and Consulting Group, he led a team of seven students to analyze the program’s data, measure its impact in the community, and provide the organization with easy-to-use data analytics tools. He has continued working with Project Somos through his undergraduate years and has joined its board of directors.

Simon hopes to quantify the most effective approaches to solutions for the people and groups he works with. “The charity I work for says ‘Use your head and your heart.’ If you can approach the problems in the world with empathy and analytics, I think that is a really important way to help a lot of people” he says.

Simon’s desire to positively impact his community is threaded through other areas of his life at MIT. He is a member of the varsity soccer team and the Phi Beta Epsilon fraternity, and has volunteered for the MIT Little Beavers Special Needs Running Club.

On the field, court, and trail

Athletics are a major part of Simon’s life, year-round. Soccer has long been his main sport; he joined the varsity soccer team as a first-year and has played ever since. In his second year with the team, Simon was recognized as an Academic All-American. He also earned the honor of NEWMAC First Team All-Conference in 2021.

Despite the long hours of practice, Simon says he is most relaxed when it’s game season. “It’s a nice, competitive outlet to have every day. You’re working with people that you like spending time with, to win games and have fun and practice to get better. Everything going on kind of fades away, and you’re just focused on playing your sport,” he explains.

Simon has also used his time at MIT to try new sports. In winter 2023, he joined the wrestling club. “I thought, ‘I’ve never done anything like this before. But maybe I’ll try it out,’” he says. “And so I tried it out knowing nothing. They were super welcoming and there were people with all experience levels, and I just really fell in love with it.” Simon also joined the MIT basketball team as a walk-on his senior year.

When not competing, Simon enjoys hiking. He recalls one of his favorite memories from the past four years being a trip to Yosemite National Park he took with friends while interning in San Francisco. There, he hiked upward of 20 miles each day. Simon also embarks on hiking trips with friends closer to campus in New Hampshire and Acadia National Park.

Social impact

Simon believes his philanthropic work has been pivotal to his experience at MIT. Through the MIT Global Research and Consulting Group, which he served as a case leader for, he has connected with charity groups around the world, including in Guatemala and South Africa.

On campus, Simon has worked to build social connections within both his school and city-wide community. During his sophomore year, he spent his Sundays with the Little Beavers Running Team, a program that pairs children from the Boston area who are on the autism spectrum with an MIT student to practice running and other sports activities. “Throughout the course of a semester when you’re working with a kid, you’re able to see their confidence and social skills improve. That’s really rewarding to me,” Simon says.

Simon is also a member of the Phi Beta Epsilon fraternity. He joined the group in his first year at MIT and has lived with the other members of the fraternity since his sophomore year. He appreciates the group’s strong focus on supporting the social and professional skills of its members. Simon served as the chapter’s president for one semester and describes his experience as “very impactful.”

“There’s something really cool about having 40 of your friends all live in a house together,” he says. “A lot of my good memories from college are of sitting around in our common rooms late at night and just talking about random stuff.”

Technical projects and helping others

Next fall, Simon will continue his studies at MIT, pursuing a master’s degree in economics. Following this, he plans to move to New York to work in finance. In the summer of 2023 he interned at BlackRock, a large finance company, where he worked on a team that invested on behalf of people looking to grow their retirement funds. Simon says, “I thought it was cool that I was able to apply things I learned in school to have an impact on a ton of different people around the country by helping them prepare for retirement.”

Simon has done similar work in past internships. In the summer after his first year at MIT, he worked for Surge Employment Solutions, a startup that connected formerly incarcerated people to jobs. His responsibility was to quantify the social impacts of the startup, which was shown to help the unemployment rate of formerly incarcerated individuals and help high-turnover businesses save money by retaining employees.

On his community work, Simon says, “There’s always a lot more similarities between people than differences. So, I think getting to know people and being able to use what I learned to help people make their lives even a little bit better is cool. You think maybe as a college student, you wouldn’t be able to do a lot to make an impact around the world. But I think even with just the computer science and economics skills that I’ve learned in college, it’s always kind of surprising to me how much of an impact you can make on people if you just put in the effort to seek out opportunities.”

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Alison Badgett named director of the Priscilla King Gray Public Service Center

Vice Chancellor for Undergraduate and Graduate Education Ian A. Waitz announced recently that Alison Badgett has been appointed the new associate dean and director of the Priscilla King Gray (PKG) Public Service Center. She succeeds Jill Bassett, who left that role to become chief of staff to Chancellor Melissa Nobles.

“Alison is a thought leader on how to integrate community-engaged learning with systematic change, making her ideally suited to actualize MIT’s mission of educating transformative leaders,” Waitz says. “I have no doubt she will make the PKG Center a model for all of higher ed, given her wealth of experience, finely honed skills, and commitment to social change.”

“I’m excited to help the PKG Center, and broader MIT community, develop a collective vision for public service education that builds on the PKG Center’s strength in social innovation programming, and leverages the Institute’s unique culture of innovation,” Badgett says. “MIT’s institutional commitment to tackling complex societal and environmental challenges, taking responsibility for outcomes and not just inputs, is exceedingly rare. I’m also especially excited to engage STEM majors, who may be less likely to enter the nonprofit or public sector, but who can have a tremendous impact on social and environmental outcomes within the systems they work.”

Badgett has over 20 years of experience leading public policy and nonprofit organizations, particularly those addressing challenging issues like affordable housing and homelessness, criminal justice, and public education. She is the founding principal of a consulting firm, From Charity to Change, which works with nonprofit leaders, educators, and philanthropists to apply systems-change strategies that target the root causes of complex social problems.

Prior to her consulting role, Badgett was executive director of the Petey Greene Program, which recruits and trains 1,000 volunteers annually from 30 universities to tutor justice-impacted students in 50 prisons and reentry programs. In addition, the program educates volunteers on the injustice of our prison system and encourages both volunteers and students to advocate for reforms.

She also served as executive director of Raise Your Hand Texas, an organization that aims to improve education by piloting innovative learning practices. During her tenure, the organization launched a five-year, $10 million initiative to showcase and scale blended learning, and a 10-year, $50 million initiative to improve teacher preparation and the status of teaching.

Before leading Raise Your Hand Texas, Badgett was executive director of several organizations related to housing and homelessness in New York and New Jersey. During that time, she developed a $3.6 million demonstration program to permanently house the chronically homeless, which served as a model for state and national replication. She also served as senior policy advisor to the governor of New Jersey, providing counsel on land use, redevelopment, and housing. 

Badgett holds a global executive EdD from the University of Southern California, an MA from Columbia University Teachers College in philosophy and education, and an BA in politics from Princeton University. 

Her appointment at the PKG Center is especially timely. Student demand for social impact experiential learning opportunities has increased significantly at MIT in recent years, and the center is expected to play a sizable role in increasing student engagement in social impact work and in helping to integrate social innovation into teaching and research.

At the same time, the Institute has made a commitment to help address complex issues with global impacts, such as climate change, economic inequality, and artificial intelligence. As part of that effort, the Office of Experiential Learning launched the Social Impact Experiential Learning Opportunity initiative last year, which has awarded nearly $1 million to fund hundreds of student opportunities. Projects cater to a broad range of interests and take place around the world — from using new computational methods to understand the role of special-interest-group funding in U.S. public policy to designing and testing a solar-powered, water-vapor condensing chamber in Madagascar.

Badgett, who is currently writing a book on re-imagining civic education at elite private schools, will begin her new role at the PKG Center in July. In the meantime, she is looking forward to bringing her experience to bear at MIT. “While leading public interest organizations was highly rewarding, I recognized that I could have a far greater impact educating future public interest leaders, and that higher education was the place to do it,” she says.

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Offering clean energy around the clock

As remarkable as the rise of solar and wind farms has been over the last 20 years, achieving complete decarbonization is going to require a host of complementary technologies. That’s because renewables offer only intermittent power. They also can’t directly provide the high temperatures necessary for many industrial processes.

Now, 247Solar is building high-temperature concentrated solar power systems that use overnight thermal energy storage to provide round-the-clock power and industrial-grade heat.

The company’s modular systems can be used as standalone microgrids for communities or to provide power in remote places like mines and farms. They can also be used in conjunction with wind and conventional solar farms, giving customers 24/7 power from renewables and allowing them to offset use of the grid.

“One of my motivations for working on this system was trying to solve the problem of intermittency,” 247Solar CEO Bruce Anderson ’69, SM ’73 says. “I just couldn’t see how we could get to zero emissions with solar photovoltaics (PV) and wind. Even with PV, wind, and batteries, we can’t get there, because there’s always bad weather, and current batteries aren’t economical over long periods. You have to have a solution that operates 24 hours a day.”

The company’s system is inspired by the design of a high-temperature heat exchanger by the late MIT Professor Emeritus David Gordon Wilson, who co-founded the company with Anderson. The company integrates that heat exchanger into what Anderson describes as a conventional, jet-engine-like turbine, enabling the turbine to produce power by circulating ambient pressure hot air with no combustion or emissions — what the company calls a first in the industry.

Here’s how the system works: Each 247Solar system uses a field of sun-tracking mirrors called heliostats to reflect sunlight to the top of a central tower. The tower features a proprietary solar receiver that heats air to around 1,000 Celsius at atmospheric pressure. The air is then used to drive 247Solar’s turbines and generate 400 kilowatts of electricity and 600 kilowatts of heat. Some of the hot air is also routed through a long-duration thermal energy storage system, where it heats solid materials that retain the heat. The stored heat is then used to drive the turbines when the sun stops shining.

“We offer round-the-clock electricity, but we also offer a combined heat and power option, with the ability to take heat up to 970 Celsius for use in industrial processes,” Anderson says. “It’s a very flexible system.”

The company’s first deployment will be with a large utility in India. If that goes well, 247Solar hopes to scale up rapidly with other utilities, corporations, and communities around the globe.

A new approach to concentrated solar

Anderson kept in touch with his MIT network after graduating in 1973. He served as the director of MIT’s Industrial Liaison Program (ILP) between 1996 and 2000 and was elected as an alumni member of the MIT Corporation in 2013. The ILP connects companies with MIT’s network of students, faculty, and alumni to facilitate innovation, and the experience changed the course of Anderson’s career.

“That was an extremely fascinating job, and from it two things happened,” Anderson says. “One is that I realized I was really an entrepreneur and was not well-suited to the university environment, and the other is that I was reminded of the countless amazing innovations coming out of MIT.”

After leaving as director, Anderson began a startup incubator where he worked with MIT professors to start companies. Eventually, one of those professors was Wilson, who had invented the new heat exchanger and a ceramic turbine. Anderson and Wilson ended up putting together a small team to commercialize the technology in the early 2000s.

Anderson had done his MIT master’s thesis on solar energy in the 1970s, and the team realized the heat exchanger made possible a novel approach to concentrated solar power. In 2010, they received a $6 million development grant from the U.S. Department of Energy. But their first solar receiver was damaged during shipping to a national laboratory for testing, and the company ran out of money.

It wasn’t until 2015 that Anderson was able to raise money to get the company back off the ground. By that time, a new high-temperature metal alloy had been developed that Anderson swapped out for Wilson’s ceramic heat exchanger.

The Covid-19 pandemic further slowed 247’s plans to build a demonstration facility at its test site in Arizona, but strong customer interest has kept the company busy. Concentrated solar power doesn’t work everywhere — Arizona’s clear sunshine is a better fit than Florida’s hazy skies, for example — but Anderson is currently in talks with communities in parts of the U.S., India, Africa, and Australia where the technology would be a good fit.

These days, the company is increasingly proposing combining its systems with traditional solar PV, which lets customers reap the benefits of low-cost solar electricity during the day while using 247’s energy at night.

“That way we can get at least 24, if not more, hours of energy from a sunny day,” Anderson says. “We’re really moving toward these hybrid systems, which work like a Prius: Sometimes you’re using one source of energy, sometimes you’re using the other.”

The company also sells its HeatStorE thermal batteries as standalone systems. Instead of being heated by the solar system, the thermal storage is heated by circulating air through an electric coil that’s been heated by electricity, either from the grid, standalone PV, or wind. The heat can be stored for nine hours or more on a single charge and then dispatched as electricity plus industrial process heat at 250 Celsius, or as heat only, up to 970 Celsius.

Anderson says 247’s thermal battery is about one-seventh the cost of lithium-ion batteries per kilowatt hour produced.

Scaling a new model

The company is keeping its system flexible for whatever path customers want to take to complete decarbonization.

In addition to 247’s India project, the company is in advanced talks with off-grid communities in the Unites States and Egypt, mining operators around the world, and the government of a small country in Africa. Anderson says the company’s next customer will likely be an off-grid community in the U.S. that currently relies on diesel generators for power.

The company has also partnered with a financial company that will allow it to access capital to fund its own projects and sell clean energy directly to customers, which Anderson says will help 247 grow faster than relying solely on selling entire systems to each customer.

As it works to scale up its deployments, Anderson believes 247 offers a solution to help customers respond to increasing pressure from governments as well as community members.

“Emerging economies in places like Africa don’t have any alternative to fossil fuels if they want 24/7 electricity,” Anderson says. “Our owning and operating costs are less than half that of diesel gen-sets. Customers today really want to stop producing emissions if they can, so you’ve got villages, mines, industries, and entire countries where the people inside are saying, ‘We can’t burn diesel anymore.’”

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