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    Advancing technology for aquaculture

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    According to the National Oceanic and Atmospheric Administration, aquaculture in the United States represents a $1.5 billion industry annually. Like land-based farming, shellfish aquaculture requires healthy seed production in order to maintain a sustainable industry. Aquaculture hatchery production of shellfish larvae — seeds — requires close monitoring to track mortality rates and assess health from the earliest stages of life. 

    Careful observation is necessary to inform production scheduling, determine effects of naturally occurring harmful bacteria, and ensure sustainable seed production. This is an essential step for shellfish hatcheries but is currently a time-consuming manual process prone to human error. 

    With funding from MIT’s Abdul Latif Jameel Water and Food Systems Lab (J-WAFS), MIT Sea Grant is working with Associate Professor Otto Cordero of the MIT Department of Civil and Environmental Engineering, Professor Taskin Padir and Research Scientist Mark Zolotas at the Northeastern University Institute for Experiential Robotics, and others at the Aquaculture Research Corporation (ARC), and the Cape Cod Commercial Fishermen’s Alliance, to advance technology for the aquaculture industry. Located on Cape Cod, ARC is a leading shellfish hatchery, farm, and wholesaler that plays a vital role in providing high-quality shellfish seed to local and regional growers.

    Two MIT students have joined the effort this semester, working with Robert Vincent, MIT Sea Grant’s assistant director of advisory services, through the Undergraduate Research Opportunities Program (UROP). 

    First-year student Unyime Usua and sophomore Santiago Borrego are using microscopy images of shellfish seed from ARC to train machine learning algorithms that will help automate the identification and counting process. The resulting user-friendly image recognition tool aims to aid aquaculturists in differentiating and counting healthy, unhealthy, and dead shellfish larvae, improving accuracy and reducing time and effort.

    Vincent explains that AI is a powerful tool for environmental science that enables researchers, industry, and resource managers to address challenges that have long been pinch points for accurate data collection, analysis, predictions, and streamlining processes. “Funding support from programs like J-WAFS enable us to tackle these problems head-on,” he says. 

    ARC faces challenges with manually quantifying larvae classes, an important step in their seed production process. “When larvae are in their growing stages they are constantly being sized and counted,” explains Cheryl James, ARC larval/juvenile production manager. “This process is critical to encourage optimal growth and strengthen the population.” 

    Developing an automated identification and counting system will help to improve this step in the production process with time and cost benefits. “This is not an easy task,” says Vincent, “but with the guidance of Dr. Zolotas at the Northeastern University Institute for Experiential Robotics and the work of the UROP students, we have made solid progress.” 

    The UROP program benefits both researchers and students. Involving MIT UROP students in developing these types of systems provides insights into AI applications that they might not have considered, providing opportunities to explore, learn, and apply themselves while contributing to solving real challenges.

    Borrego saw this project as an opportunity to apply what he’d learned in class 6.390 (Introduction to Machine Learning) to a real-world issue. “I was starting to form an idea of how computers can see images and extract information from them,” he says. “I wanted to keep exploring that.”

    Usua decided to pursue the project because of the direct industry impacts it could have. “I’m pretty interested in seeing how we can utilize machine learning to make people’s lives easier. We are using AI to help biologists make this counting and identification process easier.” While Usua wasn’t familiar with aquaculture before starting this project, she explains, “Just hearing about the hatcheries that Dr. Vincent was telling us about, it was unfortunate that not a lot of people know what’s going on and the problems that they’re facing.”

    On Cape Cod alone, aquaculture is an $18 million per year industry. But the Massachusetts Division of Marine Fisheries estimates that hatcheries are only able to meet 70–80 percent of seed demand annually, which impacts local growers and economies. Through this project, the partners aim to develop technology that will increase seed production, advance industry capabilities, and help understand and improve the hatchery microbiome.

    Borrego explains the initial challenge of having limited data to work with. “Starting out, we had to go through and label all of the data, but going through that process helped me learn a lot.” In true MIT fashion, he shares his takeaway from the project: “Try to get the best out of what you’re given with the data you have to work with. You’re going to have to adapt and change your strategies depending on what you have.”

    Usua describes her experience going through the research process, communicating in a team, and deciding what approaches to take. “Research is a difficult and long process, but there is a lot to gain from it because it teaches you to look for things on your own and find your own solutions to problems.”

    In addition to increasing seed production and reducing the human labor required in the hatchery process, the collaborators expect this project to contribute to cost savings and technology integration to support one of the most underserved industries in the United States. 

    Borrego and Usua both plan to continue their work for a second semester with MIT Sea Grant. Borrego is interested in learning more about how technology can be used to protect the environment and wildlife. Usua says she hopes to explore more projects related to aquaculture. “It seems like there’s an infinite amount of ways to tackle these issues.” More

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      “We offer another place for knowledge”

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      In the Dzaleka Refugee Camp in Malawi, Jospin Hassan didn’t have access to the education opportunities he sought. So, he decided to create his own. 

      Hassan knew the booming fields of data science and artificial intelligence could bring job opportunities to his community and help solve local challenges. After earning a spot in the 2020-21 cohort of the Certificate Program in Computer and Data Science from MIT Refugee Action Hub (ReACT), Hassan started sharing MIT knowledge and skills with other motivated learners in Dzaleka.

      MIT ReACT is now Emerging Talent, part of the Jameel World Education Lab (J-WEL) at MIT Open Learning. Currently serving its fifth cohort of global learners, Emerging Talent’s year-long certificate program incorporates high-quality computer science and data analysis coursework from MITx, professional skill building, experiential learning, apprenticeship work, and opportunities for networking with MIT’s global community of innovators. Hassan’s cohort honed their leadership skills through interactive online workshops with J-WEL and the 10-week online MIT Innovation Leadership Bootcamp. 

      “My biggest takeaway was networking, collaboration, and learning from each other,” Hassan says.

      Today, Hassan’s organization ADAI Circle offers mentorship and education programs for youth and other job seekers in the Dzaleka Refugee Camp. The curriculum encourages hands-on learning and collaboration.

      Launched in 2020, ADAI Circle aims to foster job creation and reduce poverty in Malawi through technology and innovation. In addition to their classes in data science, AI, software development, and hardware design, their Innovation Hub offers internet access to anyone in need. 

      Doing something different in the community

      Hassan first had the idea for his organization in 2018 when he reached a barrier in his own education journey. There were several programs in the Dzaleka Refugee Camp teaching learners how to code websites and mobile apps, but Hassan felt that they were limited in scope. 

      “We had good devices and internet access,” he says, “but I wanted to learn something new.” 

      Teaming up with co-founder Patrick Byamasu, Hassan and Byamasu set their sights on the longevity of AI and how that might create more jobs for people in their community. “The world is changing every day, and data scientists are in a higher demand today in various companies,” Hassan says. “For this reason, I decided to expand and share the knowledge that I acquired with my fellow refugees and the surrounding villages.”

      ADAI Circle draws inspiration from Hassan’s own experience with MIT Emerging Talent coursework, community, and training opportunities. For example, the MIT Bootcamps model is now standard practice for ADAI Circle’s annual hackathon. Hassan first introduced the hackathon to ADAI Circle students as part of his final experiential learning project of the Emerging Talent certificate program. 

      ADAI Circle’s annual hackathon is now an interactive — and effective — way to select students who will most benefit from its programs. The local schools’ curricula, Hassan says, might not provide enough of an academic challenge. “We can’t teach everyone and accommodate everyone because there are a lot of schools,” Hassan says, “but we offer another place for knowledge.” 

      The hackathon helps students develop data science and robotics skills. Before they start coding, students have to convince ADAI Circle teachers that their designs are viable, answering questions like, “What problem are you solving?” and “How will this help the community?” A community-oriented mindset is just as important to the curriculum.

      In addition to the practical skills Hassan gained from Emerging Talent, he leveraged the program’s network to help his community. Thanks to a social media connection Hassan made with the nongovernmental organization Give Internet after one of Emerging Talent’s virtual events, Give Internet brought internet access to ADAI Circle.

      Bridging the AI gap to unmet communities

      In 2023, ADAI Circle connected with another MIT Open Learning program, Responsible AI for Social Empowerment and Education (RAISE), which led to a pilot test of a project-based AI curriculum for middle school students. The Responsible AI for Computational Action (RAICA) curriculum equipped ADAI Circle students with AI skills for chatbots and natural language processing. 

      “I liked that program because it was based on what we’re teaching at the center,” Hassan says, speaking of his organization’s mission of bridging the AI gap to reach unmet communities.

      The RAICA curriculum was designed by education experts at MIT Scheller Teacher Education Program (STEP Lab) and AI experts from MIT Personal Robots group and MIT App Inventor. ADAI Circle teachers gave detailed feedback about the pilot to the RAICA team. During weekly meetings with Glenda Stump, education research scientist for RAICA and J-WEL, and Angela Daniel, teacher development specialist for RAICA, the teachers discussed their experiences, prepared for upcoming lessons, and translated the learning materials in real time. 

      “We are trying to create a curriculum that’s accessible worldwide and to students who typically have little or no access to technology,” says Mary Cate Gustafson-Quiett, curriculum design manager at STEP Lab and project manager for RAICA. “Working with ADAI and students in a refugee camp challenged us to design in more culturally and technologically inclusive ways.”

      Gustafson-Quiett says the curriculum feedback from ADAI Circle helped inform how RAICA delivers teacher development resources to accommodate learning environments with limited internet access. “They also exposed places where our team’s western ideals, specifically around individualism, crept into activities in the lesson and contrasted with their more communal cultural beliefs,” she says.

      Eager to introduce more MIT-developed AI resources, Hassan also shared MIT RAISE’s Day of AI curricula with ADAI Circle teachers. The new ChatGPT module gave students the chance to level up their chatbot programming skills that they gained from the RAICA module. Some of the advanced students are taking initiative to use ChatGPT API to create their own projects in education.

      “We don’t want to tell them what to do, we want them to come up with their own ideas,” Hassan says.

      Although ADAI Circle faces many challenges, Hassan says his team is addressing them one by one. Last year, they didn’t have electricity in their Innovation Hub, but they solved that. This year, they achieved a stable internet connection that’s one of the fastest in Malawi. Next up, they are hoping to secure more devices for their students, create more jobs, and add additional hubs throughout the community. The work is never done, but Hassan is starting to see the impact that ADAI Circle is making. 

      “For those who want to learn data science, let’s let them learn,” Hassan says. More

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      Generating the policy of tomorrow

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      As first-year students in the Social and Engineering Systems (SES) doctoral program within the MIT Institute for Data, Systems, and Society (IDSS), Eric Liu and Ashely Peake share an interest in investigating housing inequality issues.

      They also share a desire to dive head-first into their research.

      “In the first year of your PhD, you’re taking classes and still getting adjusted, but we came in very eager to start doing research,” Liu says.

      Liu, Peake, and many others found an opportunity to do hands-on research on real-world problems at the MIT Policy Hackathon, an initiative organized by students in IDSS, including the Technology and Policy Program (TPP). The weekend-long, interdisciplinary event — now in its sixth year — continues to gather hundreds of participants from around the globe to explore potential solutions to some of society’s greatest challenges.

      This year’s theme, “Hack-GPT: Generating the Policy of Tomorrow,” sought to capitalize on the popularity of generative AI (like the chatbot ChatGPT) and the ways it is changing how we think about technical and policy-based challenges, according to Dansil Green, a second-year TPP master’s student and co-chair of the event.

      “We encouraged our teams to utilize and cite these tools, thinking about the implications that generative AI tools have on their different challenge categories,” Green says.

      After 2022’s hybrid event, this year’s organizers pivoted back to a virtual-only approach, allowing them to increase the overall number of participants in addition to increasing the number of teams per challenge by 20 percent.

      “Virtual allows you to reach more people — we had a high number of international participants this year — and it helps reduce some of the costs,” Green says. “I think going forward we are going to try and switch back and forth between virtual and in-person because there are different benefits to each.”

      “When the magic hits”

      Liu and Peake competed in the housing challenge category, where they could gain research experience in their actual field of study. 

      “While I am doing housing research, I haven’t necessarily had a lot of opportunities to work with actual housing data before,” says Peake, who recently joined the SES doctoral program after completing an undergraduate degree in applied math last year. “It was a really good experience to get involved with an actual data problem, working closer with Eric, who’s also in my lab group, in addition to meeting people from MIT and around the world who are interested in tackling similar questions and seeing how they think about things differently.”

      Joined by Adrian Butterton, a Boston-based paralegal, as well as Hudson Yuen and Ian Chan, two software engineers from Canada, Liu and Peake formed what would end up being the winning team in their category: “Team Ctrl+Alt+Defeat.” They quickly began organizing a plan to address the eviction crisis in the United States.

      “I think we were kind of surprised by the scope of the question,” Peake laughs. “In the end, I think having such a large scope motivated us to think about it in a more realistic kind of way — how could we come up with a solution that was adaptable and therefore could be replicated to tackle different kinds of problems.”

      Watching the challenge on the livestream together on campus, Liu says they immediately went to work, and could not believe how quickly things came together.

      “We got our challenge description in the evening, came out to the purple common area in the IDSS building and literally it took maybe an hour and we drafted up the entire project from start to finish,” Liu says. “Then our software engineer partners had a dashboard built by 1 a.m. — I feel like the hackathon really promotes that really fast dynamic work stream.”

      “People always talk about the grind or applying for funding — but when that magic hits, it just reminds you of the part of research that people don’t talk about, and it was really a great experience to have,” Liu adds.

      A fresh perspective

      “We’ve organized hackathons internally at our company and they are great for fostering innovation and creativity,” says Letizia Bordoli, senior AI product manager at Veridos, a German-based identity solutions company that provided this year’s challenge in Data Systems for Human Rights. “It is a great opportunity to connect with talented individuals and explore new ideas and solutions that we might not have thought about.”

      The challenge provided by Veridos was focused on finding innovative solutions to universal birth registration, something Bordoli says only benefited from the fact that the hackathon participants were from all over the world.

      “Many had local and firsthand knowledge about certain realities and challenges [posed by the lack of] birth registration,” Bordoli says. “It brings fresh perspectives to existing challenges, and it gave us an energy boost to try to bring innovative solutions that we may not have considered before.”

      New frontiers

      Alongside the housing and data systems for human rights challenges was a challenge in health, as well as a first-time opportunity to tackle an aerospace challenge in the area of space for environmental justice.

      “Space can be a very hard challenge category to do data-wise since a lot of data is proprietary, so this really developed over the last few months with us having to think about how we could do more with open-source data,” Green explains. “But I am glad we went the environmental route because it opened the challenge up to not only space enthusiasts, but also environment and climate people.”

      One of the participants to tackle this new challenge category was Yassine Elhallaoui, a system test engineer from Norway who specializes in AI solutions and has 16 years of experience working in the oil and gas fields. Elhallaoui was a member of Team EcoEquity, which proposed an increase in policies supporting the use of satellite data to ensure proper evaluation and increase water resiliency for vulnerable communities.

      “The hackathons I have participated in in the past were more technical,” Elhallaoui says. “Starting with [MIT Science and Technology Policy Institute Director Kristen Kulinowski’s] workshop about policy writers and the solutions they came up with, and the analysis they had to do … it really changed my perspective on what a hackathon can do.”

      “A policy hackathon is something that can make real changes in the world,” she adds. More

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      Blueprint Labs launches a charter school research collaborative

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      Over the past 30 years, charter schools have emerged as a prominent yet debated public school option. According to the National Center for Education Statistics, 7 percent of U.S. public school students were enrolled in charter schools in 2021, up from 4 percent in 2010. Amid this expansion, families and policymakers want to know more about charter school performance and its systemic impacts. While researchers have evaluated charter schools’ short-term effects on student outcomes, significant knowledge gaps still exist. 

      MIT Blueprint Labs aims to fill those gaps through its Charter School Research Collaborative, an initiative that brings together practitioners, policymakers, researchers, and funders to make research on charter schools more actionable, rigorous, and efficient. The collaborative will create infrastructure to streamline and fund high-quality, policy-relevant charter research. 

      Joshua Angrist, MIT Ford Professor of Economics and a Blueprint Labs co-founder and director, says that Blueprint Labs hopes “to increase [its] impact by working with a larger group of academic and practitioner partners.” A nonpartisan research lab, Blueprint’s mission is to produce the most rigorous evidence possible to inform policy and practice. Angrist notes, “The debate over charter schools is not always fact-driven. Our goal at the lab is to bring convincing evidence into these discussions.”

      Collaborative kickoff

      The collaborative launched with a two-day kickoff in November. Blueprint Labs welcomed researchers, practitioners, funders, and policymakers to MIT to lay the groundwork for the collaborative. Over 80 participants joined the event, including leaders of charter school organizations, researchers at top universities and institutes, and policymakers and advocates from a variety of organizations and education agencies. 

      Through a series of panels, presentations, and conversations, participants including Rhode Island Department of Education Commissioner Angélica Infante-Green, CEO of Noble Schools Constance Jones, former Knowledge is Power Program CEO Richard Barth, president and CEO of National Association of Charter School Authorizers Karega Rausch, and many others discussed critical topics in the charter school space. These conversations influenced the collaborative’s research agenda. 

      Several sessions also highlighted how to ensure that the research process includes diverse voices to generate actionable evidence. Panelists noted that researchers should be aware of the demands placed on practitioners and should carefully consider community contexts. In addition, collaborators should treat each other as equal partners. 

      Parag Pathak, the Class of 1922 Professor of Economics at MIT and a Blueprint Labs co-founder and director, explained the kickoff’s aims. “One of our goals today is to begin to forge connections between [attendees]. We hope that [their] conversations are the launching point for future collaborations,” he stated. Pathak also shared the next steps for the collaborative: “Beginning next year, we’ll start investing in new research using the agenda [developed at this event] as our guide. We will also support new partnerships between researchers and practitioners.”

      Research agenda

      The discussions at the kickoff informed the collaborative’s research agenda. A recent paper summarizing existing lottery-based research on charter school effectiveness by Sarah Cohodes, an associate professor of public policy at the University of Michigan, and Susha Roy, an associate policy researcher at the RAND Corp., also guides the agenda. Their review finds that in randomized evaluations, many charter schools increase students’ academic achievement. However, researchers have not yet studied charter schools’ impacts on long-term, behavioral, or health outcomes in depth, and rigorous, lottery-based research is currently limited to a handful of urban centers. 

      The current research agenda focuses on seven topics:

      the long-term effects of charter schools;
      the effect of charters on non-test score outcomes;
      which charter school practices have the largest effect on performance;
      how charter performance varies across different contexts;
      how charter school effects vary with demographic characteristics and student background;
      how charter schools impact non-student outcomes, like teacher retention; and
      how system-level factors, such as authorizing practices, impact charter school performance.
      As diverse stakeholders’ priorities continue to shift and the collaborative progresses, the research agenda will continue to evolve.

      Information for interested partners

      Opportunities exist for charter leaders, policymakers, researchers, and funders to engage with the collaborative. Stakeholders can apply for funding, help shape the research agenda, and develop new research partnerships. A competitive funding process will open this month.

      Those interested in receiving updates on the collaborative can fill out this form. Please direct questions to chartercollab@mitblueprintlabs.org. More

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      Bridging the gap between preschool policy, practice, and research

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      Preschool in the United States has grown dramatically in the past several decades. From 1970 to 2018, preschool enrollment increased from 38 percent to 64 percent of eligible students. Fourteen states are currently discussing preschool expansion, with seven likely to pass some form of universal eligibility within the next calendar year. Amid this expansion, families, policymakers, and practitioners want to better understand preschools’ impacts and the factors driving preschool quality. 

      To address these and other questions, MIT Blueprint Labs recently held a Preschool Research Convening that brought researchers, funders, practitioners, and policymakers to Nashville, Tennessee, to discuss the future of preschool research. Parag Pathak, the Class of 1922 Professor of Economics at MIT and a Blueprint Labs co-founder and director, opened by sharing the goals of the convening: “Our goals for the next two days are to identify pressing, unanswered research questions and connect researchers, practitioners, policymakers, and funders. We also hope to craft a compelling research agenda.”

      Pathak added, “Given preschool expansion nationwide, we believe now is the moment to centralize our efforts and create knowledge to inform pressing decisions. We aim to generate rigorous preschool research that will lead to higher-quality and more equitable preschool.”

      Over 75 participants hailing from universities, early childhood education organizations, school districts, state education departments, and national policy organizations attended the convening, held Nov. 13-14. Through panels, presentations, and conversations, participants discussed essential subjects in the preschool space, built the foundations for valuable partnerships, and formed an actionable and inclusive research agenda.

      Research presented

      Among research works presented was a recent paper by Blueprint Labs affiliate Jesse Bruhn, an assistant professor of economics at Brown University and co-author Emily Emick, also of Brown, reviewing the state of lottery-based preschool research. They found that random evaluations from the past 60 years demonstrate that preschool improves children’s short-run academic outcomes, but those effects fade over time. However, positive impacts re-emerge in the long term through improved outcomes like high school graduation and college enrollment. Limited rigorous research studies children’s behavioral outcomes or the factors that lead to high-quality preschool, though trends from preliminary research suggest that full-day programs, language immersion programs, and specific curricula may benefit children.  

      An earlier Blueprint Labs study that was also presented at the convening is the only recent lottery-based study to provide insight on preschool’s long-term impacts. The work, conducted by Pathak and two others, reveals that enrolling in Boston Public Schools’ universal preschool program boosts children’s likelihood of graduating high school and enrolling in college. Yet, the preschool program had little detectable impact on elementary, middle, and high school state standardized test scores. Students who attended Boston preschool were less likely to be suspended or incarcerated in high school. However, research on preschool’s impacts on behavioral outcomes is limited; it remains an important area for further study. Future work could also fill in other gaps in research, such as access, alternative measures of student success, and variation across geographic contexts and student populations.

      More data sought

      State policy leaders also spoke at the event, including Lisa Roy, executive director of the Colorado Department of Early Childhood, and Sarah Neville-Morgan, deputy superintendent in the Opportunities for All Branch at the California Department of Education. Local practitioners, such as Elsa Holguín, president and CEO of the Denver Preschool Program, and Kristin Spanos, CEO of First 5 Alameda County, as well as national policy leaders including Lauren Hogan, managing director of policy and professional advancement at the National Association for the Education of Young Children, also shared their perspectives. 

      In panel discussions held throughout the kickoff, practitioners, policymakers, and researchers shared their perspectives on pressing questions for future research, including: What practices define high-quality preschool? How does preschool affect family systems and the workforce? How can we expand measures of effectiveness to move beyond traditional assessments? What can we learn from preschool’s differential impacts across time, settings, models, and geographies?

      Panelists also discussed the need for reliable data, sharing that “the absence of data allows the status quo to persist.” Several sessions focused on involving diverse stakeholders in the research process, highlighting the need for transparency, sensitivity to community contexts, and accessible communication about research findings.

      On the second day of the Preschool Research Convening, Pathak shared with attendees, “One of our goals… is to forge connections between all of you in this room and support new partnerships between researchers and practitioners. We hope your conversations are the launching pad for future collaborations.” Jason Sachs, the deputy director of early learning at the Bill and Melinda Gates Foundation and former director of early childhood at Boston Public Schools, provided closing remarks.

      The convening laid the groundwork for a research agenda and new research partnerships that can help answer questions about what works, in what context, for which kids, and under which conditions. Answers to these questions will be fundamental to ensure preschool expands in the most evidence-informed and equitable way possible.

      With this goal in mind, Blueprint Labs aims to create a new Preschool Research Collaborative to equip practitioners, policymakers, funders, and researchers with rigorous, actionable evidence on preschool performance. Pathak states, “We hope this collaborative will foster evidence-based decision-making that improves children’s short- and long-term outcomes.” The connections and research agenda formed at the Preschool Research Convening are the first steps toward achieving that goal. More

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      Leveraging language to understand machines

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      Natural language conveys ideas, actions, information, and intent through context and syntax; further, there are volumes of it contained in databases. This makes it an excellent source of data to train machine-learning systems on. Two master’s of engineering students in the 6A MEng Thesis Program at MIT, Irene Terpstra ’23 and Rujul Gandhi ’22, are working with mentors in the MIT-IBM Watson AI Lab to use this power of natural language to build AI systems.

      As computing is becoming more advanced, researchers are looking to improve the hardware that they run on; this means innovating to create new computer chips. And, since there is literature already available on modifications that can be made to achieve certain parameters and performance, Terpstra and her mentors and advisors Anantha Chandrakasan, MIT School of Engineering dean and the Vannevar Bush Professor of Electrical Engineering and Computer Science, and IBM’s researcher Xin Zhang, are developing an AI algorithm that assists in chip design.

      “I’m creating a workflow to systematically analyze how these language models can help the circuit design process. What reasoning powers do they have, and how can it be integrated into the chip design process?” says Terpstra. “And then on the other side, if that proves to be useful enough, [we’ll] see if they can automatically design the chips themselves, attaching it to a reinforcement learning algorithm.”

      To do this, Terpstra’s team is creating an AI system that can iterate on different designs. It means experimenting with various pre-trained large language models (like ChatGPT, Llama 2, and Bard), using an open-source circuit simulator language called NGspice, which has the parameters of the chip in code form, and a reinforcement learning algorithm. With text prompts, researchers will be able to query how the physical chip should be modified to achieve a certain goal in the language model and produced guidance for adjustments. This is then transferred into a reinforcement learning algorithm that updates the circuit design and outputs new physical parameters of the chip.

      “The final goal would be to combine the reasoning powers and the knowledge base that is baked into these large language models and combine that with the optimization power of the reinforcement learning algorithms and have that design the chip itself,” says Terpstra.

      Rujul Gandhi works with the raw language itself. As an undergraduate at MIT, Gandhi explored linguistics and computer sciences, putting them together in her MEng work. “I’ve been interested in communication, both between just humans and between humans and computers,” Gandhi says.

      Robots or other interactive AI systems are one area where communication needs to be understood by both humans and machines. Researchers often write instructions for robots using formal logic. This helps ensure that commands are being followed safely and as intended, but formal logic can be difficult for users to understand, while natural language comes easily. To ensure this smooth communication, Gandhi and her advisors Yang Zhang of IBM and MIT assistant professor Chuchu Fan are building a parser that converts natural language instructions into a machine-friendly form. Leveraging the linguistic structure encoded by the pre-trained encoder-decoder model T5, and a dataset of annotated, basic English commands for performing certain tasks, Gandhi’s system identifies the smallest logical units, or atomic propositions, which are present in a given instruction.

      “Once you’ve given your instruction, the model identifies all the smaller sub-tasks you want it to carry out,” Gandhi says. “Then, using a large language model, each sub-task can be compared against the available actions and objects in the robot’s world, and if any sub-task can’t be carried out because a certain object is not recognized, or an action is not possible, the system can stop right there to ask the user for help.”

      This approach of breaking instructions into sub-tasks also allows her system to understand logical dependencies expressed in English, like, “do task X until event Y happens.” Gandhi uses a dataset of step-by-step instructions across robot task domains like navigation and manipulation, with a focus on household tasks. Using data that are written just the way humans would talk to each other has many advantages, she says, because it means a user can be more flexible about how they phrase their instructions.

      Another of Gandhi’s projects involves developing speech models. In the context of speech recognition, some languages are considered “low resource” since they might not have a lot of transcribed speech available, or might not have a written form at all. “One of the reasons I applied to this internship at the MIT-IBM Watson AI Lab was an interest in language processing for low-resource languages,” she says. “A lot of language models today are very data-driven, and when it’s not that easy to acquire all of that data, that’s when you need to use the limited data efficiently.” 

      Speech is just a stream of sound waves, but humans having a conversation can easily figure out where words and thoughts start and end. In speech processing, both humans and language models use their existing vocabulary to recognize word boundaries and understand the meaning. In low- or no-resource languages, a written vocabulary might not exist at all, so researchers can’t provide one to the model. Instead, the model can make note of what sound sequences occur together more frequently than others, and infer that those might be individual words or concepts. In Gandhi’s research group, these inferred words are then collected into a pseudo-vocabulary that serves as a labeling method for the low-resource language, creating labeled data for further applications.

      The applications for language technology are “pretty much everywhere,” Gandhi says. “You could imagine people being able to interact with software and devices in their native language, their native dialect. You could imagine improving all the voice assistants that we use. You could imagine it being used for translation or interpretation.” More

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      “MIT can give you ‘superpowers’”

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      Speaking at the virtual MITx MicroMasters Program Joint Completion Celebration last summer, Diogo da Silva Branco Magalhães described watching a Spider-Man movie with his 8-year-old son and realizing that his son thought MIT was a fictional entity that existed only in the Marvel universe.

      “I had to tell him that MIT also exists in the real world, and that some of the programs are available online for everyone,” says da Silva Branco Magalhães, who earned his credential in the MicroMasters in Statistics and Data Science program. “You don’t need to be a superhero to participate in an MIT program, but MIT can give you ‘superpowers.’ In my case, the superpower that I was looking to acquire was a better understanding of the key technologies that are shaping the future of transportation.

      Part of MIT Open Learning, the MicroMasters programs have drawn in almost 1.4 million learners, spanning nearly every country in the world. More than 7,500 people have earned their credentials across the MicroMasters programs, including: Statistics and Data Science; Supply Chain Management; Data, Economics, and Design of Policy; Principles of Manufacturing; and Finance. 

      Earning his MicroMasters credential not only gave da Silva Branco Magalhães a strong foundation to tackle more complex transportation problems, but it also opened the door to pursuing an accelerated graduate degree via a Northwestern University online program.

      Learners who earn their MicroMasters credentials gain the opportunity to apply to and continue their studies at a pathway school. The MicroMasters in Statistics and Data Science credential can be applied as credit for a master’s program at more than 30 universities, as well as MIT’s PhD Program in Social and Engineering Systems. Da Silva Branco Magalhães, originally from Portugal and now based in Australia, seized this opportunity and enrolled in Northwestern University’s Master’s in Data Science for MIT MicroMasters Credential Holders. 

      The pathway to an enhanced career

      The pathway model launched in 2016 with the MicroMasters in Supply Chain Management. Now, there are over 50 pathway institutions that offer more than 100 different programs for master’s degrees. With pathway institutions located around the world, MicroMasters credential holders can obtain master’s degrees from local residential or virtual programs, at a location convenient to them. They can receive credit for their MicroMasters courses upon acceptance, providing flexibility for online programs and also shortening the time needed on site for residential programs.

      “The pathways expand opportunities for learners, and also help universities attract a broader range of potential students, which can enrich their programs,” says Dana Doyle, senior director for the MicroMasters Program at MIT Open Learning. “This is a tangible way we can achieve our mission of expanding education access.”

      Da Silva Branco Magalhães began the MicroMasters in Statistics and Data Science program in 2020, ultimately completing the program in 2022.

      “After having worked for 20 years in the transportation sector in various roles, I realized I was no longer equipped as a professional to deal with the new technologies that were set to disrupt the mobility sector,” says da Silva Branco Magalhães. “It became clear to me that data and AI were the driving forces behind new products and services such as autonomous vehicles, on-demand transport, or mobility as a service, but I didn’t really understand how data was being used to achieve these outcomes, so I needed to improve my knowledge.”

      July 2023 MicroMasters Program Joint Completion Celebration for SCM, DEDP, PoM, SDS, and FinVideo: MIT Open Learning

      The MicroMasters in Statistics and Data Science was developed by the MIT Institute for Data, Systems, and Society and MITx. Credential holders are required to complete four courses equivalent to graduate-level courses in statistics and data science at MIT and a capstone exam comprising four two-hour proctored exams.

      “The content is world-class,” da Silva Branco Magalhães says of the program. “Even the most complex concepts were explained in a very intuitive way. The exercises and the capstone exam are challenging and stimulating — and MIT-level — which makes this credential highly valuable in the market.”

      Da Silva Branco Magalhães also found the discussion forum very useful, and valued conversations with his colleagues, noting that many of these discussions later continued after completion of the program.

      Gaining analysis and leadership skills

      Now in the Northwestern pathway program, da Silva Branco Magalhães finds that the MicroMasters in Statistics and Data Science program prepared him well for this next step in his studies. The nine-course, accelerated, online master’s program is designed to offer the same depth and rigor of Northwestern’s 12-course MS in Data Science program, aiming to help students build essential analysis and leadership skills that can be directly implemented into the professional realm. Students learn how to make reliable predictions using traditional statistics and machine learning methods.

      Da Silva Branco Magalhães says he has appreciated the remote nature of the Northwestern program, as he started it in France and then completed the first three courses in Australia. He also values the high number of elective courses, allowing students to design the master’s program according to personal preferences and interests.

      “I want to be prepared to meet the challenges and seize the opportunities that AI and data science technologies will bring to the professional realm,” he says. “With this credential, there are no limits to what you can achieve in the field of data science.” More

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      Forging climate connections across the Institute

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      Climate change is the ultimate cross-cutting issue: Not limited to any one discipline, it ranges across science, technology, policy, culture, human behavior, and well beyond. The response to it likewise requires an all-of-MIT effort.

      Now, to strengthen such an effort, a new grant program spearheaded by the Climate Nucleus, the faculty committee charged with the oversight and implementation of Fast Forward: MIT’s Climate Action Plan for the Decade, aims to build up MIT’s climate leadership capacity while also supporting innovative scholarship on diverse climate-related topics and forging new connections across the Institute.

      Called the Fast Forward Faculty Fund (F^4 for short), the program has named its first cohort of six faculty members after issuing its inaugural call for proposals in April 2023. The cohort will come together throughout the year for climate leadership development programming and networking. The program provides financial support for graduate students who will work with the faculty members on the projects — the students will also participate in leadership-building activities — as well as $50,000 in flexible, discretionary funding to be used to support related activities. 

      “Climate change is a crisis that truly touches every single person on the planet,” says Noelle Selin, co-chair of the nucleus and interim director of the Institute for Data, Systems, and Society. “It’s therefore essential that we build capacity for every member of the MIT community to make sense of the problem and help address it. Through the Fast Forward Faculty Fund, our aim is to have a cohort of climate ambassadors who can embed climate everywhere at the Institute.”

      F^4 supports both faculty who would like to begin doing climate-related work, as well as faculty members who are interested in deepening their work on climate. The program has the core goal of developing cohorts of F^4 faculty and graduate students who, in addition to conducting their own research, will become climate leaders at MIT, proactively looking for ways to forge new climate connections across schools, departments, and disciplines.

      One of the projects, “Climate Crisis and Real Estate: Science-based Mitigation and Adaptation Strategies,” led by Professor Siqi Zheng of the MIT Center for Real Estate in collaboration with colleagues from the MIT Sloan School of Management, focuses on the roughly 40 percent of carbon dioxide emissions that come from the buildings and real estate sector. Zheng notes that this sector has been slow to respond to climate change, but says that is starting to change, thanks in part to the rising awareness of climate risks and new local regulations aimed at reducing emissions from buildings.

      Using a data-driven approach, the project seeks to understand the efficient and equitable market incentives, technology solutions, and public policies that are most effective at transforming the real estate industry. Johnattan Ontiveros, a graduate student in the Technology and Policy Program, is working with Zheng on the project.

      “We were thrilled at the incredible response we received from the MIT faculty to our call for proposals, which speaks volumes about the depth and breadth of interest in climate at MIT,” says Anne White, nucleus co-chair and vice provost and associate vice president for research. “This program makes good on key commitments of the Fast Forward plan, supporting cutting-edge new work by faculty and graduate students while helping to deepen the bench of climate leaders at MIT.”

      During the 2023-24 academic year, the F^4 faculty and graduate student cohorts will come together to discuss their projects, explore opportunities for collaboration, participate in climate leadership development, and think proactively about how to deepen interdisciplinary connections among MIT community members interested in climate change.

      The six inaugural F^4 awardees are:

      Professor Tristan Brown, History Section: Humanistic Approaches to the Climate Crisis  

      With this project, Brown aims to create a new community of practice around narrative-centric approaches to environmental and climate issues. Part of a broader humanities initiative at MIT, it brings together a global working group of interdisciplinary scholars, including Serguei Saavedra (Department of Civil and Environmental Engineering) and Or Porath (Tel Aviv University; Religion), collectively focused on examining the historical and present links between sacred places and biodiversity for the purposes of helping governments and nongovernmental organizations formulate better sustainability goals. Boyd Ruamcharoen, a PhD student in the History, Anthropology, and Science, Technology, and Society (HASTS) program, will work with Brown on this project.

      Professor Kerri Cahoy, departments of Aeronautics and Astronautics and Earth, Atmospheric, and Planetary Sciences (AeroAstro): Onboard Autonomous AI-driven Satellite Sensor Fusion for Coastal Region Monitoring

      The motivation for this project is the need for much better data collection from satellites, where technology can be “20 years behind,” says Cahoy. As part of this project, Cahoy will pursue research in the area of autonomous artificial intelligence-enabled rapid sensor fusion (which combines data from different sensors, such as radar and cameras) onboard satellites to improve understanding of the impacts of climate change, specifically sea-level rise and hurricanes and flooding in coastal regions. Graduate students Madeline Anderson, a PhD student in electrical engineering and computer science (EECS), and Mary Dahl, a PhD student in AeroAstro, will work with Cahoy on this project.

      Professor Priya Donti, Department of Electrical Engineering and Computer Science: Robust Reinforcement Learning for High-Renewables Power Grids 

      With renewables like wind and solar making up a growing share of electricity generation on power grids, Donti’s project focuses on improving control methods for these distributed sources of electricity. The research will aim to create a realistic representation of the characteristics of power grid operations, and eventually inform scalable operational improvements in power systems. It will “give power systems operators faith that, OK, this conceptually is good, but it also actually works on this grid,” says Donti. PhD candidate Ana Rivera from EECS is the F^4 graduate student on the project.

      Professor Jason Jackson, Department of Urban Studies and Planning (DUSP): Political Economy of the Climate Crisis: Institutions, Power and Global Governance

      This project takes a political economy approach to the climate crisis, offering a distinct lens to examine, first, the political governance challenge of mobilizing climate action and designing new institutional mechanisms to address the global and intergenerational distributional aspects of climate change; second, the economic challenge of devising new institutional approaches to equitably finance climate action; and third, the cultural challenge — and opportunity — of empowering an adaptive socio-cultural ecology through traditional knowledge and local-level social networks to achieve environmental resilience. Graduate students Chen Chu and Mrinalini Penumaka, both PhD students in DUSP, are working with Jackson on the project.

      Professor Haruko Wainwright, departments of Nuclear Science and Engineering (NSE) and Civil and Environmental Engineering: Low-cost Environmental Monitoring Network Technologies in Rural Communities for Addressing Climate Justice 

      This project will establish a community-based climate and environmental monitoring network in addition to a data visualization and analysis infrastructure in rural marginalized communities to better understand and address climate justice issues. The project team plans to work with rural communities in Alaska to install low-cost air and water quality, weather, and soil sensors. Graduate students Kay Whiteaker, an MS candidate in NSE, and Amandeep Singh, and MS candidate in System Design and Management at Sloan, are working with Wainwright on the project, as is David McGee, professor in earth, atmospheric, and planetary sciences.

      Professor Siqi Zheng, MIT Center for Real Estate and DUSP: Climate Crisis and Real Estate: Science-based Mitigation and Adaptation Strategies 

      See the text above for the details on this project. More

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      J-PAL North America and Results for America announce 18 collaborations with state and local governments

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      J-PAL North America and Results for America have announced 18 new partnerships with state and local governments across the country through their Leveraging Evidence and Evaluation for Equitable Recovery (LEVER) programming, which launched in April of this year. 

      As state and local leaders leverage federal relief funding to invest in their communities, J-PAL North America and Results for America are providing in-depth support to agencies in using data, evaluation, and evidence to advance effective and equitable government programming for generations to come. The 18 new collaborators span the contiguous United States and represent a wide range of pressing and innovative uses of federal Covid-19 recovery funding.

      These partnerships are a key component of the LEVER program, run by J-PAL North America — a regional office of MIT’s Abdul Latif Jameel Poverty Action Lab (J-PAL) — and Results for America — a nonprofit organization that helps government agencies harness the power of evidence and data. Through 2024, LEVER will continue to provide a suite of resources, training, and evaluation design services to prepare state and local government agencies to rigorously evaluate their own programs and to harness existing evidence in developing programs and policies using federal recovery dollars.

      J-PAL North America is working with four leading government agencies following a call for proposals to the LEVER Evaluation Incubator in June. These agencies will work with J-PAL staff to design randomized evaluations to understand the causal impact of important programs that contribute to their jurisdictions’ recovery from Covid-19.

      Connecticut’s Medicaid office, operating out of the state’s Department of Social Services, is working to improve vaccine access and awareness among youth. “Connecticut Medicaid is thrilled to work with J-PAL North America. The technical expertise and training that we receive will expand our knowledge during ‘testing and learning’ interventions that improve the health of our members,” says Gui Woolston, the director of Medicaid and Division of Health Services. 

      Athens-Clarke County Unified Government is invested in evaluating programming for youth development and violence prevention implemented by the Boys and Girls Club of Athens. Their goal is “to measure and transparently communicate program impact,” explains Paige Seago, the data and outcomes coordinator for the American Rescue Plan Act. “The ability to continually iterate and tailor programs to better meet community goals is crucial to long-term success.”

      The County of San Diego’s newly formed Office of Evaluation, Performance, and Analytics is evaluating a pilot program providing rental subsidies for older adults. “Randomized evaluation can help us understand if rent subsidies will help prevent seniors from becoming homeless and will give us useful information about how to move forward,” says Chief Evaluation Officer Ricardo Basurto-Dávila. 

      In King County, Washington, the Executive Climate Office is planning to evaluate efforts to increase equitable access to household energy efficiency programs. “Because of J-PAL’s support, we have confidence that we can reduce climate impacts and extend home electrification benefits to lower-income homeowners in King County — homeowners who otherwise may not have the ability to participate in the clean energy transition,” says King County Climate Director Marissa Aho.

      Fourteen additional state and local agencies are working with Results for America as part of the LEVER Training Sprint. Together, they will develop policies that catalyze sustainable evidence building within government. 

      Jurisdictions selected for the Training Sprint represent government leaders at the city, county, and state levels — all of whom are committed to creating an evaluation framework for policy that will prioritize evidence-based decision-making across the country. Over the course of 10 weeks, with access to tools and coaching, each team will develop an internal implementation policy by embedding key evaluation and evidence practices into their jurisdiction’s decision-making processes. Participants will finish the Training Sprint with a robust decision-making framework that translates their LEVER implementation policies into actionable planning guidance. 

      Government leaders will utilize the LEVER Training Sprint to build a culture of data and evidence focused on leveraging evaluation policies to invest in delivering tangible results for their residents. About their participation in the LEVER Training Sprint, Dana Williams from Denver, Colorado says, “Impact evaluation is such an integral piece to understanding the past, present, and future. I’m excited to participate in the LEVER Training Sprint to better inform and drive evidence-based programming in Denver.”

      The Training Sprint is a part of a growing movement to ground government innovation in data and evidence. Kermina Hanna from the State of New Jersey notes, “It’s vital that we cement a data-driven commitment to equity in government operations, and I’m really excited for this opportunity to develop a national network of colleagues in government who share this passion and dedication to responsive public service.”

      Jurisdictions selected for the Training Sprint are: 

      Boston, Massachusetts;
      Carlsbad, California;
      Connecticut;
      Dallas, Texas;
      Denver City/County, Colorado;
      Fort Collins, Colorado;
      Guilford County, North Carolina;
      King County, Washington;
      Long Beach, California;
      Los Angeles, California;
      New Jersey;
      New Mexico;
      Pittsburgh, Pennsylvania; and
      Washington County, Oregon.
      Those interested in learning more can fill out the LEVER intake form. Please direct any questions about the Evaluation Incubator to Louise Geraghty and questions about the Training Sprint to Chelsea Powell. More