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    Community members receive 2024 MIT Excellence Awards, Collier Medal, and Staff Award for Distinction in Service

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    On Wednesday, June 5, 13 individuals and four teams were awarded MIT Excellence Awards — the highest awards for staff at the Institute. Colleagues holding signs, waving pompoms, and cheering gathered in Kresge Auditorium to show their support for the honorees. In addition to the Excellence Awards, staff members were honored with the Collier Medal, the Staff Award for Distinction in Service, and the Gordon Y. Billard Award. The Collier Medal honors the memory of Officer Sean Collier, who gave his life protecting and serving MIT; it celebrates an individual or group whose actions demonstrate the importance of community. The Staff Award for Distinction in Service is presented to a staff member whose service results in a positive lasting impact on the Institute.The Gordon Y. Billard Award is given annually to staff, faculty, or an MIT-affiliated individual(s) who has given “special service of outstanding merit performed for the Institute.” This year, for the first time, this award was presented at the MIT Excellence Awards and Collier Medal celebration. The 2024 MIT Excellence Award recipients and their award categories are: Innovative Solutions Nanotechnology Material Core Staff, Koch Institute for Integrative Cancer Research, Office of the Vice President for Research (Margaret Bisher, Giovanni de Nola, David Mankus, and Dong Soo Yun)Bringing Out the Best Salvatore Ieni James Kelsey Lauren PouchakServing Our Community Megan Chester Alessandra Davy-Falconi David Randall Days Weekend Team, Department of Custodial Services, Department of Facilities: Karen Melisa Betancourth, Ana Guerra Chavarria, Yeshi Khando, Joao Pacheco, and Kevin Salazar IMES/HST Academic Office Team, Institute for Medical Engineering and Science, School of Engineering: Traci Anderson, Joseph R. Stein, and Laurie Ward Team Leriche, Department of Custodial Services, Department of Facilities: Anthony Anzalone, David Solomon Carrasco, Larrenton Forrest, Michael Leriche, and Joe VieiraEmbracing Diversity, Equity, and Inclusion Bhaskar Pant Jessica TamOutstanding Contributor Paul W. Barone Marcia G. Davidson Steven Kooi Tianjiao Lei Andrew H. Mack

    2024 MIT Excellence Awards + Collier Medal Ceremony

    The 2024 Collier Medal recipient was Benjamin B. Lewis, a graduate student in the Institute for Data, Systems and Society in the MIT Schwarzman College of Computing. Last spring, he founded the Cambridge branch of End Overdose, a nonprofit dedicated to reducing drug-related overdose deaths. Through his efforts, more than 600 members of the Greater Boston community, including many at MIT, have been trained to administer lifesaving treatment at critical moments.This year’s recipient of the 2024 Staff Award for Distinction in Service was Diego F. Arango (Department of Custodial Services, Department of Facilities), daytime custodian in Building 46. He was nominated by no fewer than 36 staff, faculty, students, and researchers for creating a positive working environment and for offering “help whenever, wherever, and to whomever needs it.”Three community members were honored with a 2024 Gordon Y. Billard AwardDeborah G. Douglas, senior director of collections and curator of science and technology, MIT MuseumRonald Hasseltine, assistant provost for research administration, Office of the Vice President for ResearchRichard K. Lester, vice provost for international activities and Japan Steel Industry Professor of Nuclear Science and Engineering, School of EngineeringPresenters included President Sally Kornbluth; MIT Chief of Police John DiFava and Deputy Chief Steven DeMarco; Vice President for Human Resources Ramona Allen; Executive Vice President and Treasurer Glen Shor; Provost Cynthia Barnhart; Lincoln Laboratory director Eric Evans; Chancellor Melissa Nobles; and Dean of the School of Engineering Anantha Chandrakasan.Visit the MIT Human Resources website for more information about the award recipients, categories, and to view photos and video of the event. More

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      MIT-Takeda Program wraps up with 16 publications, a patent, and nearly two dozen projects completed

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      When the Takeda Pharmaceutical Co. and the MIT School of Engineering launched their collaboration focused on artificial intelligence in health care and drug development in February 2020, society was on the cusp of a globe-altering pandemic and AI was far from the buzzword it is today.As the program concludes, the world looks very different. AI has become a transformative technology across industries including health care and pharmaceuticals, while the pandemic has altered the way many businesses approach health care and changed how they develop and sell medicines.For both MIT and Takeda, the program has been a game-changer.When it launched, the collaborators hoped the program would help solve tangible, real-world problems. By its end, the program has yielded a catalog of new research papers, discoveries, and lessons learned, including a patent for a system that could improve the manufacturing of small-molecule medicines.Ultimately, the program allowed both entities to create a foundation for a world where AI and machine learning play a pivotal role in medicine, leveraging Takeda’s expertise in biopharmaceuticals and the MIT researchers’ deep understanding of AI and machine learning.“The MIT-Takeda Program has been tremendously impactful and is a shining example of what can be accomplished when experts in industry and academia work together to develop solutions,” says Anantha Chandrakasan, MIT’s chief innovation and strategy officer, dean of the School of Engineering, and the Vannevar Bush Professor of Electrical Engineering and Computer Science. “In addition to resulting in research that has advanced how we use AI and machine learning in health care, the program has opened up new opportunities for MIT faculty and students through fellowships, funding, and networking.”What made the program unique was that it was centered around several concrete challenges spanning drug development that Takeda needed help addressing. MIT faculty had the opportunity to select the projects based on their area of expertise and general interest, allowing them to explore new areas within health care and drug development.“It was focused on Takeda’s toughest business problems,” says Anne Heatherington, Takeda’s research and development chief data and technology officer and head of its Data Sciences Institute.“They were problems that colleagues were really struggling with on the ground,” adds Simon Davies, the executive director of the MIT-Takeda Program and Takeda’s global head of statistical and quantitative sciences. Takeda saw an opportunity to collaborate with MIT’s world-class researchers, who were working only a few blocks away. Takeda, a global pharmaceutical company with global headquarters in Japan, has its global business units and R&D center just down the street from the Institute.As part of the program, MIT faculty were able to select what issues they were interested in working on from a group of potential Takeda projects. Then, collaborative teams including MIT researchers and Takeda employees approached research questions in two rounds. Over the course of the program, collaborators worked on 22 projects focused on topics including drug discovery and research, clinical drug development, and pharmaceutical manufacturing. Over 80 MIT students and faculty joined more than 125 Takeda researchers and staff on teams addressing these research questions.The projects centered around not only hard problems, but also the potential for solutions to scale within Takeda or within the biopharmaceutical industry more broadly.Some of the program’s findings have already resulted in wider studies. One group’s results, for instance, showed that using artificial intelligence to analyze speech may allow for earlier detection of frontotemporal dementia, while making that diagnosis more quickly and inexpensively. Similar algorithmic analyses of speech in patients diagnosed with ALS may also help clinicians understand the progression of that disease. Takeda is continuing to test both AI applications.Other discoveries and AI models that resulted from the program’s research have already had an impact. Using a physical model and AI learning algorithms can help detect particle size, mix, and consistency for powdered, small-molecule medicines, for instance, speeding up production timelines. Based on their research under the program, collaborators have filed for a patent for that technology.For injectable medicines like vaccines, AI-enabled inspections can also reduce process time and false rejection rates. Replacing human visual inspections with AI processes has already shown measurable impact for the pharmaceutical company.Heatherington adds, “our lessons learned are really setting the stage for what we’re doing next, really embedding AI and gen-AI [generative AI] into everything that we do moving forward.”Over the course of the program, more than 150 Takeda researchers and staff also participated in educational programming organized by the Abdul Latif Jameel Clinic for Machine Learning in Health. In addition to providing research opportunities, the program funded 10 students through SuperUROP, the Advanced Undergraduate Research Opportunities Program, as well as two cohorts from the DHIVE health-care innovation program, part of the MIT Sandbox Innovation Fund Program.Though the formal program has ended, certain aspects of the collaboration will continue, such as the MIT-Takeda Fellows, which supports graduate students as they pursue groundbreaking research related to health and AI. During its run, the program supported 44 MIT-Takeda Fellows and will continue to support MIT students through an endowment fund. Organic collaboration between MIT and Takeda researchers will also carry forward. And the programs’ collaborators are working to create a model for similar academic and industry partnerships to widen the impact of this first-of-its-kind collaboration.  More

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      MIT Faculty Founder Initiative announces three winners of entrepreneurship awards

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      Patients with intractable cancers, chronic pain sufferers, and people who depend on battery-powered medical implants may all benefit from the ideas presented at the 2023-24 MIT-Royalty Pharma Prize Competition’s recent awards. This year’s top prizes went to researchers and biotech entrepreneurs Anne Carpenter, Frederike Petzschner, and Betar Gallant ’08, SM ’10, PhD ’13.MIT Faculty Founder Initiative Executive Director Kit Hickey MBA ’13 describes the time and hard work the three awardees and other finalists devoted to the initiative and its mission of cultivating female faculty in biotech to cross the chasm between laboratory research and its clinical application.“They have taken the first brave step of getting off the bench when they already work seven days a week. They have carved out time from their facilities, from their labs, from their lives in order to put themselves out there and leap into entrepreneurship,” Hickey says. “They’ve done it because they each want to see their innovations out in the world improving patients’ lives.”Carpenter, senior director of the Imaging Platform at the Broad Institute of MIT and Harvard, where she is also an institute scientist, won the competition’s $250,000 2023-24 MIT-Royalty Pharma Faculty Founder Prize Competition Grand Prize. Carpenter specializes in using microscopy imaging of cells and computational methods such as machine learning to accelerate the identification of chemical compounds with therapeutic potential to, for instance, shrink tumors. The identified compounds are then tested in biological assays that model the tumor ecosystem to see how the compounds would perform on actual tumors.Carpenter’s startup, SyzOnc, launched in April, a feat Carpenter associates with the assistance provided by the MIT Faculty Founder Initiative. Participants in the program receive mentorship, stipends, and advice from industry experts, as well as help with incorporating, assembling a management team, fundraising, and intellectual property strategy.“The program offered key insights and input at major decision points that gave us the momentum to open our doors,” Carpenter says, adding that participating “offered validation of our scientific ideas and business plan. That kind of credibility is really helpful to raising funding, particularly for those starting their first company.”Carpenter says she and her team will employ “the best biological and computational advancements to develop new therapies to fight tumors such as sarcoma, pancreatic cancer, and glioblastoma, which currently have dismal survival rates.”The MIT Faculty Founder Initiative was begun in 2020 by the School of Engineering and the Martin Trust Center for MIT Entrepreneurship, based on research findings by Sangeeta Bhatia, the Wilson Professor of Health Sciences and Technology, professor of electrical engineering and computer science, and faculty director of the MIT Faculty Founder Initiative; Susan Hockfield, MIT Corporation life member, MIT president emerita, and professor of neuroscience; and Nancy Hopkins, professor emerita of biology. An investigation they conducted showed that only about 9 percent of MIT’s 250 biotech startups were started by women, whereas women made up 22 percent of the faculty, as was presented in a 2021 MIT Faculty Newsletter.That data showed that “technologies from female labs were not getting out in the world, resulting in lost potential,” Hickey says.“The MIT Faculty Founder Initiative plays a pivotal role in MIT’s entrepreneurship ecosystem. It elevates visionary faculty working on solutions in biotech by providing them with critical mentorship and resources, ensuring these solutions can be rapidly scaled to market,” says Anantha Chandrakasan, MIT’s chief innovation and strategy officer, dean of engineering, and Vannevar Bush Professor of Electrical Engineering and Computer Science.The MIT Faculty Founder Initiative Prize Competition was launched in 2021. At this year’s competition, the judges represented academia, health care, biotech, and financial investment. In addition to awarding a grand prize, the competition also distributed two $100,000 prizes, one to a researcher from Brown University, the first university to collaborate with MIT in the entrepreneurship program.This year’s winner of the $100,000 2023-24 MIT-Royalty Pharma Faculty Founder Prize Competition Runner-Up Prize was Frederike Petzschner, assistant professor at the Carney Institute for Brain Science at Brown, for her SOMA startup’s digital pain management system, which helps sufferers to manage and relieve chronic pain.“We leverage cutting-edge technology to provide precision care, focusing specifically on personalized cognitive interventions tailored to each patient’s unique needs,” she says.With her startup on the verge of incorporating, Petzschner says, “without the Faculty Finder Initiative, our startup would still be pursuing commercialization, but undoubtedly at a much earlier and perhaps less structured stage.”“The constant support from the program organizers and our mentors was truly transformative,” she says.Gallant, associate professor of mechanical engineering at MIT and winner of the $100,000 2023-24 MIT-Royalty Pharma Faculty Founder Prize Competition Breakthrough Prize, is leading the startup Halogen. An expert on advanced battery technologies, Gallant and her team have developed high-density battery storage to improve the lifetime and performance of such medical devices as pacemakers.“If you can extend lifetime, you’re talking about longer times between invasive replacement surgeries, which really affects patient quality of life,” Gallant told MIT News in a 2022 interview.Jim Reddoch, executive vice president and chief scientific officer of sponsor Royalty Pharma, emphasized his company’s support for both the competition and the MIT Faculty Finder Initiative program.“Royalty Pharma is thrilled to support the 2023-2024 MIT-Royalty Pharma Prize Competition and accelerate life sciences innovation at leading research institutions such as MIT and Brown,” Reddoch says. “By supporting the amazing female entrepreneurs in this program, we hope to catalyze more ideas from the lab to biotech companies and eventually into the hands of patients.”Bhatia has referred to the MIT Faculty Founder Initiative as a “playbook” on how to direct female faculty’s high-impact technologies that are not being commercialized into the world of health care.“To me, changing the game means that when you have an invention in your lab, you’re connected enough to the ecosystem to know when it should be a company, and to know who to call and how to get your first investors and how to quickly catalyze your team — and you’re off to the races,” Bhatia says. “Every one one of those inventions can be a medicine as quickly as possible. That’s the future I imagine.”Co-founder Hockfield referred to MIT’s role in promoting entrepreneurship in remarks at the award ceremony, alluding to Brown University’s having joined the effort.“MIT has always been a leader in entrepreneurship,” Hockfield says. “Part of leading is sharing with the world. The collaboration with Brown University for this cohort shows that MIT can share our approach with the world, allowing other universities to follow our model of supporting academic entrepreneurship.”Hickey says that when she and Bhatia asked 30 female faculty members three years ago why they were not commercializing their technologies, many said they had no access to the appropriate networks of mentors, investors, role models, and business partners necessary to begin the journey.“We encourage you to become this network that has been missing,” Hickey told the awards event audience, which included an array of leaders in the biotech world. “Get to know our amazing faculty members and continue to support them. Become a part of this movement.” More

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      Six MIT students selected as spring 2024 MIT-Pillar AI Collective Fellows

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      The MIT-Pillar AI Collective has announced six fellows for the spring 2024 semester. With support from the program, the graduate students, who are in their final year of a master’s or PhD program, will conduct research in the areas of AI, machine learning, and data science with the aim of commercializing their innovations.

      Launched by MIT’s School of Engineering and Pillar VC in 2022, the MIT-Pillar AI Collective supports faculty, postdocs, and students conducting research on AI, machine learning, and data science. Supported by a gift from Pillar VC and administered by the MIT Deshpande Center for Technological Innovation, the mission of the program is to advance research toward commercialization.

      The spring 2024 MIT-Pillar AI Collective Fellows are:

      Yasmeen AlFaraj

      Yasmeen AlFaraj is a PhD candidate in chemistry whose interest is in the application of data science and machine learning to soft materials design to enable next-generation, sustainable plastics, rubber, and composite materials. More specifically, she is applying machine learning to the design of novel molecular additives to enable the low-cost manufacturing of chemically deconstructable thermosets and composites. AlFaraj’s work has led to the discovery of scalable, translatable new materials that could address thermoset plastic waste. As a Pillar Fellow, she will pursue bringing this technology to market, initially focusing on wind turbine blade manufacturing and conformal coatings. Through the Deshpande Center for Technological Innovation, AlFaraj serves as a lead for a team developing a spinout focused on recyclable versions of existing high-performance thermosets by incorporating small quantities of a degradable co-monomer. In addition, she participated in the National Science Foundation Innovation Corps program and recently graduated from the Clean Tech Open, where she focused on enhancing her business plan, analyzing potential markets, ensuring a complete IP portfolio, and connecting with potential funders. AlFaraj earned a BS in chemistry from University of California at Berkeley.

      Ruben Castro Ornelas

      Ruben Castro Ornelas is a PhD student in mechanical engineering who is passionate about the future of multipurpose robots and designing the hardware to use them with AI control solutions. Combining his expertise in programming, embedded systems, machine design, reinforcement learning, and AI, he designed a dexterous robotic hand capable of carrying out useful everyday tasks without sacrificing size, durability, complexity, or simulatability. Ornelas’s innovative design holds significant commercial potential in domestic, industrial, and health-care applications because it could be adapted to hold everything from kitchenware to delicate objects. As a Pillar Fellow, he will focus on identifying potential commercial markets, determining the optimal approach for business-to-business sales, and identifying critical advisors. Ornelas served as co-director of StartLabs, an undergraduate entrepreneurship club at MIT, where he earned an BS in mechanical engineering.

      Keeley Erhardt

      Keeley Erhardt is a PhD candidate in media arts and sciences whose research interests lie in the transformative potential of AI in network analysis, particularly for entity correlation and hidden link detection within and across domains. She has designed machine learning algorithms to identify and track temporal correlations and hidden signals in large-scale networks, uncovering online influence campaigns originating from multiple countries. She has similarly demonstrated the use of graph neural networks to identify coordinated cryptocurrency accounts by analyzing financial time series data and transaction dynamics. As a Pillar Fellow, Erhardt will pursue the potential commercial applications of her work, such as detecting fraud, propaganda, money laundering, and other covert activity in the finance, energy, and national security sectors. She has had internships at Google, Facebook, and Apple and held software engineering roles at multiple tech unicorns. Erhardt earned an MEng in electrical engineering and computer science and a BS in computer science, both from MIT.

      Vineet Jagadeesan Nair

      Vineet Jagadeesan Nair is a PhD candidate in mechanical engineering whose research focuses on modeling power grids and designing electricity markets to integrate renewables, batteries, and electric vehicles. He is broadly interested in developing computational tools to tackle climate change. As a Pillar Fellow, Nair will explore the application of machine learning and data science to power systems. Specifically, he will experiment with approaches to improve the accuracy of forecasting electricity demand and supply with high spatial-temporal resolution. In collaboration with Project Tapestry @ Google X, he is also working on fusing physics-informed machine learning with conventional numerical methods to increase the speed and accuracy of high-fidelity simulations. Nair’s work could help realize future grids with high penetrations of renewables and other clean, distributed energy resources. Outside academics, Nair is active in entrepreneurship, most recently helping to organize the 2023 MIT Global Startup Workshop in Greece. He earned an MS in computational science and engineering from MIT, an MPhil in energy technologies from Cambridge University as a Gates Scholar, and a BS in mechanical engineering and a BA in economics from University of California at Berkeley.

      Mahdi Ramadan

      Mahdi Ramadan is a PhD candidate in brain and cognitive sciences whose research interests lie at the intersection of cognitive science, computational modeling, and neural technologies. His work uses novel unsupervised methods for learning and generating interpretable representations of neural dynamics, capitalizing on recent advances in AI, specifically contrastive and geometric deep learning techniques capable of uncovering the latent dynamics underlying neural processes with high fidelity. As a Pillar Fellow, he will leverage these methods to gain a better understanding of dynamical models of muscle signals for generative motor control. By supplementing current spinal prosthetics with generative AI motor models that can streamline, speed up, and correct limb muscle activations in real time, as well as potentially using multimodal vision-language models to infer the patients’ high-level intentions, Ramadan aspires to build truly scalable, accessible, and capable commercial neuroprosthetics. Ramadan’s entrepreneurial experience includes being the co-founder of UltraNeuro, a neurotechnology startup, and co-founder of Presizely, a computer vision startup. He earned a BS in neurobiology from University of Washington.

      Rui (Raymond) Zhou

      Rui (Raymond) Zhou is a PhD candidate in mechanical engineering whose research focuses on multimodal AI for engineering design. As a Pillar Fellow, he will advance models that could enable designers to translate information in any modality or combination of modalities into comprehensive 2D and 3D designs, including parametric data, component visuals, assembly graphs, and sketches. These models could also optimize existing human designs to accomplish goals such as improving ergonomics or reducing drag coefficient. Ultimately, Zhou aims to translate his work into a software-as-a-service platform that redefines product design across various sectors, from automotive to consumer electronics. His efforts have the potential to not only accelerate the design process but also reduce costs, opening the door to unprecedented levels of customization, idea generation, and rapid prototyping. Beyond his academic pursuits, Zhou founded UrsaTech, a startup that integrates AI into education and engineering design. He earned a BS in electrical engineering and computer sciences from University of California at Berkeley. More

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      Three MIT students selected as inaugural MIT-Pillar AI Collective Fellows

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      MIT-Pillar AI Collective has announced three inaugural fellows for the fall 2023 semester. With support from the program, the graduate students, who are in their final year of a master’s or PhD program, will conduct research in the areas of artificial intelligence, machine learning, and data science with the aim of commercializing their innovations.

      Launched by MIT’s School of Engineering and Pillar VC in 2022, the MIT-Pillar AI Collective supports faculty, postdocs, and students conducting research on AI, machine learning, and data science. Supported by a gift from Pillar VC and administered by the MIT Deshpande Center for Technological Innovation, the mission of the program is to advance research toward commercialization.

      The fall 2023 MIT-Pillar AI Collective Fellows are:

      Alexander Andonian SM ’21 is a PhD candidate in electrical engineering and computer science whose research interests lie in computer vision, deep learning, and artificial intelligence. More specifically, he is focused on building a generalist, multimodal AI scientist driven by generative vision-language model agents capable of proposing scientific hypotheses, running computational experiments, evaluating supporting evidence, and verifying conclusions in the same way as a human researcher or reviewer. Such an agent could be trained to optimally distill and communicate its findings for human consumption and comprehension. Andonian’s work holds the promise of creating a concrete foundation for rigorously building and holistically testing the next-generation autonomous AI agent for science. In addition to his research, Andonian is the CEO and co-founder of Reelize, a startup that offers a generative AI video tool that effortlessly turns long videos into short clips — and originated from his business coursework and was supported by MIT Sandbox. Andonian is also a founding AI researcher at Poly AI, an early-stage YC-backed startup building AI design tools. Andonian earned an SM from MIT and a BS in neuroscience, physics, and mathematics from Bates College.

      Daniel Magley is a PhD candidate in the Harvard-MIT Program in Health Sciences and Technology who is passionate about making a healthy, fully functioning mind and body a reality for all. His leading-edge research is focused on developing a swallowable wireless thermal imaging capsule that could be used in treating and monitoring inflammatory bowel diseases and their manifestations, such as Crohn’s disease. Providing increased sensitivity and eliminating the need for bowel preparation, the capsule has the potential to vastly improve treatment efficacy and overall patient experience in routine monitoring. The capsule has completed animal studies and is entering human studies at Mass General Brigham, where Magley leads a team of engineers in the hospital’s largest translational research lab, the Tearney Lab. Following the human pilot studies, the largest technological and regulatory risks will be cleared for translation. Magley will then begin focusing on a multi-site study to get the device into clinics, with the promise of benefiting patients across the country. Magley earned a BS in electrical engineering from Caltech.

      Madhumitha Ravichandra is a PhD candidate interested in advancing heat transfer and surface engineering techniques to enhance the safety and performance of nuclear energy systems and reduce their environmental impacts. Leveraging her deep knowledge of the integration of explainable AI with high-throughput autonomous experimentation, she seeks to transform the development of radiation-hardened (rad-hard) sensors, which could potentially withstand and function amidst radiation levels that would render conventional sensors useless. By integrating explainable AI with high-throughput autonomous experimentation, she aims to rapidly iterate designs, test under varied conditions, and ensure that the final product is both robust and transparent in its operations. Her work in this space could shift the paradigm in rad-hard sensor development, addressing a glaring void in the market and redefining standards, ensuring that nuclear and space applications are safer, more efficient, and at the cutting edge of technological progress. Ravichandran earned a BTech in mechanical engineering from SASTRA University, India. More

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      Rewarding excellence in open data

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      The second annual MIT Prize for Open Data, which included a $2,500 cash prize, was recently awarded to 10 individual and group research projects. Presented jointly by the School of Science and the MIT Libraries, the prize highlights the value of open data — research data that is openly accessible and reusable — at the Institute. The prize winners and 12 honorable mention recipients were honored at the Open Data @ MIT event held Oct. 24 at Hayden Library. 

      Conceived by Chris Bourg, director of MIT Libraries, and Rebecca Saxe, associate dean of the School of Science and the John W. Jarve (1978) Professor of Brain and Cognitive Sciences, the prize program was launched in 2022. It recognizes MIT-affiliated researchers who use or share open data, create infrastructure for open data sharing, or theorize about open data. Nominations were solicited from across the Institute, with a focus on trainees: undergraduate and graduate students, postdocs, and research staff. 

      “The prize is explicitly aimed at early-career researchers,” says Bourg. “Supporting and encouraging the next generation of researchers will help ensure that the future of scholarship is characterized by a norm of open sharing.”

      The 2023 awards were presented at a celebratory event held during International Open Access Week. Winners gave five-minute presentations on their projects and the role that open data plays in their research. The program also included remarks from Bourg and Anne White, School of Engineering Distinguished Professor of Engineering, vice provost, and associate vice president for research administration. White reflected on the ways in which MIT has demonstrated its values with the open sharing of research and scholarship and acknowledged the efforts of the honorees and advocates gathered at the event: “Thank you for the active role you’re all playing in building a culture of openness in research,” she said. “It benefits us all.” 

      Winners were chosen from more than 80 nominees, representing all five MIT schools, the MIT Schwarzman College of Computing, and several research centers across the Institute. A committee composed of faculty, staff, and graduate students made the selections:

      Hammaad Adam, graduate student in the Institute for Data, Systems, and Society, accepted on behalf of the team behind Organ Retrieval and Collection of Health Information for Donation (ORCHID), the first ever multi-center dataset dedicated to the organ procurement process. ORCHID provides the first opportunity to quantitatively analyze organ procurement organization decisions and identify operational inefficiencies.
      Adam Atanas, postdoc in the Department of Brain and Cognitive Sciences (BCS), and Jungsoo Kim, graduate student in BCS, created WormWideWeb.org. The site, allowing researchers to easily browse and download C. elegans whole-brain datasets, will be useful to C. elegans neuroscientists and theoretical/computational neuroscientists. 
      Paul Berube, research scientist in the Department of Civil and Environmental Engineering, and Steven Biller, assistant professor of biological sciences at Wellesley College, won for “Unlocking Marine Microbiomes with Open Data.” Open data of genomes and metagenomes for marine ecosystems, with a focus on cyanobacteria, leverage the power of contemporaneous data from GEOTRACES and other long-standing ocean time-series programs to provide underlying information to answer questions about marine ecosystem function. 
      Jack Cavanagh, Sarah Kopper, and Diana Horvath of the Abdul Latif Jameel Poverty Action Lab (J-PAL) were recognized for J-PAL’s Data Publication Infrastructure, which includes a trusted repository of open-access datasets, a dedicated team of data curators, and coding tools and training materials to help other teams publish data in an efficient and ethical manner. 
      Jerome Patrick Cruz, graduate student in the Department of Political Science, won for OpenAudit, leveraging advances in natural language processing and machine learning to make data in public audit reports more usable for academics and policy researchers, as well as governance practitioners, watchdogs, and reformers. This work was done in collaboration with colleagues at Ateneo de Manila University in the Philippines. 
      Undergraduate student Daniel Kurlander created a tool for planetary scientists to rapidly access and filter images of the comet 67P/Churyumov-Gerasimenko. The web-based tool enables searches by location and other properties, does not require a time-intensive download of a massive dataset, allows analysis of the data independent of the speed of one’s computer, and does not require installation of a complex set of programs. 
      Halie Olson, postdoc in BCS, was recognized for sharing data from a functional magnetic resonance imaging (fMRI) study on language processing. The study used video clips from “Sesame Street” in which researchers manipulated the comprehensibility of the speech stream, allowing them to isolate a “language response” in the brain.
      Thomas González Roberts, graduate student in the Department of Aeronautics and Astronautics, won for the International Telecommunication Union Compliance Assessment Monitor. This tool combats the heritage of secrecy in outer space operations by creating human- and machine-readable datasets that succinctly describe the international agreements that govern satellite operations. 
      Melissa Kline Struhl, research scientist in BCS, was recognized for Children Helping Science, a free, open-source platform for remote studies with babies and children that makes it possible for researchers at more than 100 institutions to conduct reproducible studies. 
      JS Tan, graduate student in the Department of Urban Studies and Planning, developed the Collective Action in Tech Archive in collaboration with Nataliya Nedzhvetskaya of the University of California at Berkeley. It is an open database of all publicly recorded collective actions taken by workers in the global tech industry. 
      A complete list of winning projects and honorable mentions, including links to the research data, is available on the MIT Libraries website. More

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      2023-24 Takeda Fellows: Advancing research at the intersection of AI and health

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      The School of Engineering has selected 13 new Takeda Fellows for the 2023-24 academic year. With support from Takeda, the graduate students will conduct pathbreaking research ranging from remote health monitoring for virtual clinical trials to ingestible devices for at-home, long-term diagnostics.

      Now in its fourth year, the MIT-Takeda Program, a collaboration between MIT’s School of Engineering and Takeda, fuels the development and application of artificial intelligence capabilities to benefit human health and drug development. Part of the Abdul Latif Jameel Clinic for Machine Learning in Health, the program coalesces disparate disciplines, merges theory and practical implementation, combines algorithm and hardware innovations, and creates multidimensional collaborations between academia and industry.

      The 2023-24 Takeda Fellows are:

      Adam Gierlach

      Adam Gierlach is a PhD candidate in the Department of Electrical Engineering and Computer Science. Gierlach’s work combines innovative biotechnology with machine learning to create ingestible devices for advanced diagnostics and delivery of therapeutics. In his previous work, Gierlach developed a non-invasive, ingestible device for long-term gastric recordings in free-moving patients. With the support of a Takeda Fellowship, he will build on this pathbreaking work by developing smart, energy-efficient, ingestible devices powered by application-specific integrated circuits for at-home, long-term diagnostics. These revolutionary devices — capable of identifying, characterizing, and even correcting gastrointestinal diseases — represent the leading edge of biotechnology. Gierlach’s innovative contributions will help to advance fundamental research on the enteric nervous system and help develop a better understanding of gut-brain axis dysfunctions in Parkinson’s disease, autism spectrum disorder, and other prevalent disorders and conditions.

      Vivek Gopalakrishnan

      Vivek Gopalakrishnan is a PhD candidate in the Harvard-MIT Program in Health Sciences and Technology. Gopalakrishnan’s goal is to develop biomedical machine-learning methods to improve the study and treatment of human disease. Specifically, he employs computational modeling to advance new approaches for minimally invasive, image-guided neurosurgery, offering a safe alternative to open brain and spinal procedures. With the support of a Takeda Fellowship, Gopalakrishnan will develop real-time computer vision algorithms that deliver high-quality, 3D intraoperative image guidance by extracting and fusing information from multimodal neuroimaging data. These algorithms could allow surgeons to reconstruct 3D neurovasculature from X-ray angiography, thereby enhancing the precision of device deployment and enabling more accurate localization of healthy versus pathologic anatomy.

      Hao He

      Hao He is a PhD candidate in the Department of Electrical Engineering and Computer Science. His research interests lie at the intersection of generative AI, machine learning, and their applications in medicine and human health, with a particular emphasis on passive, continuous, remote health monitoring to support virtual clinical trials and health-care management. More specifically, He aims to develop trustworthy AI models that promote equitable access and deliver fair performance independent of race, gender, and age. In his past work, He has developed monitoring systems applied in clinical studies of Parkinson’s disease, Alzheimer’s disease, and epilepsy. Supported by a Takeda Fellowship, He will develop a novel technology for the passive monitoring of sleep stages (using radio signaling) that seeks to address existing gaps in performance across different demographic groups. His project will tackle the problem of imbalance in available datasets and account for intrinsic differences across subpopulations, using generative AI and multi-modality/multi-domain learning, with the goal of learning robust features that are invariant to different subpopulations. He’s work holds great promise for delivering advanced, equitable health-care services to all people and could significantly impact health care and AI.

      Chengyi Long

      Chengyi Long is a PhD candidate in the Department of Civil and Environmental Engineering. Long’s interdisciplinary research integrates the methodology of physics, mathematics, and computer science to investigate questions in ecology. Specifically, Long is developing a series of potentially groundbreaking techniques to explain and predict the temporal dynamics of ecological systems, including human microbiota, which are essential subjects in health and medical research. His current work, supported by a Takeda Fellowship, is focused on developing a conceptual, mathematical, and practical framework to understand the interplay between external perturbations and internal community dynamics in microbial systems, which may serve as a key step toward finding bio solutions to health management. A broader perspective of his research is to develop AI-assisted platforms to anticipate the changing behavior of microbial systems, which may help to differentiate between healthy and unhealthy hosts and design probiotics for the prevention and mitigation of pathogen infections. By creating novel methods to address these issues, Long’s research has the potential to offer powerful contributions to medicine and global health.

      Omar Mohd

      Omar Mohd is a PhD candidate in the Department of Electrical Engineering and Computer Science. Mohd’s research is focused on developing new technologies for the spatial profiling of microRNAs, with potentially important applications in cancer research. Through innovative combinations of micro-technologies and AI-enabled image analysis to measure the spatial variations of microRNAs within tissue samples, Mohd hopes to gain new insights into drug resistance in cancer. This work, supported by a Takeda Fellowship, falls within the emerging field of spatial transcriptomics, which seeks to understand cancer and other diseases by examining the relative locations of cells and their contents within tissues. The ultimate goal of Mohd’s current project is to find multidimensional patterns in tissues that may have prognostic value for cancer patients. One valuable component of his work is an open-source AI program developed with collaborators at Beth Israel Deaconess Medical Center and Harvard Medical School to auto-detect cancer epithelial cells from other cell types in a tissue sample and to correlate their abundance with the spatial variations of microRNAs. Through his research, Mohd is making innovative contributions at the interface of microsystem technology, AI-based image analysis, and cancer treatment, which could significantly impact medicine and human health.

      Sanghyun Park

      Sanghyun Park is a PhD candidate in the Department of Mechanical Engineering. Park specializes in the integration of AI and biomedical engineering to address complex challenges in human health. Drawing on his expertise in polymer physics, drug delivery, and rheology, his research focuses on the pioneering field of in-situ forming implants (ISFIs) for drug delivery. Supported by a Takeda Fellowship, Park is currently developing an injectable formulation designed for long-term drug delivery. The primary goal of his research is to unravel the compaction mechanism of drug particles in ISFI formulations through comprehensive modeling and in-vitro characterization studies utilizing advanced AI tools. He aims to gain a thorough understanding of this unique compaction mechanism and apply it to drug microcrystals to achieve properties optimal for long-term drug delivery. Beyond these fundamental studies, Park’s research also focuses on translating this knowledge into practical applications in a clinical setting through animal studies specifically aimed at extending drug release duration and improving mechanical properties. The innovative use of AI in developing advanced drug delivery systems, coupled with Park’s valuable insights into the compaction mechanism, could contribute to improving long-term drug delivery. This work has the potential to pave the way for effective management of chronic diseases, benefiting patients, clinicians, and the pharmaceutical industry.

      Huaiyao Peng

      Huaiyao Peng is a PhD candidate in the Department of Biological Engineering. Peng’s research interests are focused on engineered tissue, microfabrication platforms, cancer metastasis, and the tumor microenvironment. Specifically, she is advancing novel AI techniques for the development of pre-cancer organoid models of high-grade serous ovarian cancer (HGSOC), an especially lethal and difficult-to-treat cancer, with the goal of gaining new insights into progression and effective treatments. Peng’s project, supported by a Takeda Fellowship, will be one of the first to use cells from serous tubal intraepithelial carcinoma lesions found in the fallopian tubes of many HGSOC patients. By examining the cellular and molecular changes that occur in response to treatment with small molecule inhibitors, she hopes to identify potential biomarkers and promising therapeutic targets for HGSOC, including personalized treatment options for HGSOC patients, ultimately improving their clinical outcomes. Peng’s work has the potential to bring about important advances in cancer treatment and spur innovative new applications of AI in health care. 

      Priyanka Raghavan

      Priyanka Raghavan is a PhD candidate in the Department of Chemical Engineering. Raghavan’s research interests lie at the frontier of predictive chemistry, integrating computational and experimental approaches to build powerful new predictive tools for societally important applications, including drug discovery. Specifically, Raghavan is developing novel models to predict small-molecule substrate reactivity and compatibility in regimes where little data is available (the most realistic regimes). A Takeda Fellowship will enable Raghavan to push the boundaries of her research, making innovative use of low-data and multi-task machine learning approaches, synthetic chemistry, and robotic laboratory automation, with the goal of creating an autonomous, closed-loop system for the discovery of high-yielding organic small molecules in the context of underexplored reactions. Raghavan’s work aims to identify new, versatile reactions to broaden a chemist’s synthetic toolbox with novel scaffolds and substrates that could form the basis of essential drugs. Her work has the potential for far-reaching impacts in early-stage, small-molecule discovery and could help make the lengthy drug-discovery process significantly faster and cheaper.

      Zhiye Song

      Zhiye “Zoey” Song is a PhD candidate in the Department of Electrical Engineering and Computer Science. Song’s research integrates cutting-edge approaches in machine learning (ML) and hardware optimization to create next-generation, wearable medical devices. Specifically, Song is developing novel approaches for the energy-efficient implementation of ML computation in low-power medical devices, including a wearable ultrasound “patch” that captures and processes images for real-time decision-making capabilities. Her recent work, conducted in collaboration with clinicians, has centered on bladder volume monitoring; other potential applications include blood pressure monitoring, muscle diagnosis, and neuromodulation. With the support of a Takeda Fellowship, Song will build on that promising work and pursue key improvements to existing wearable device technologies, including developing low-compute and low-memory ML algorithms and low-power chips to enable ML on smart wearable devices. The technologies emerging from Song’s research could offer exciting new capabilities in health care, enabling powerful and cost-effective point-of-care diagnostics and expanding individual access to autonomous and continuous medical monitoring.

      Peiqi Wang

      Peiqi Wang is a PhD candidate in the Department of Electrical Engineering and Computer Science. Wang’s research aims to develop machine learning methods for learning and interpretation from medical images and associated clinical data to support clinical decision-making. He is developing a multimodal representation learning approach that aligns knowledge captured in large amounts of medical image and text data to transfer this knowledge to new tasks and applications. Supported by a Takeda Fellowship, Wang will advance this promising line of work to build robust tools that interpret images, learn from sparse human feedback, and reason like doctors, with potentially major benefits to important stakeholders in health care.

      Oscar Wu

      Haoyang “Oscar” Wu is a PhD candidate in the Department of Chemical Engineering. Wu’s research integrates quantum chemistry and deep learning methods to accelerate the process of small-molecule screening in the development of new drugs. By identifying and automating reliable methods for finding transition state geometries and calculating barrier heights for new reactions, Wu’s work could make it possible to conduct the high-throughput ab initio calculations of reaction rates needed to screen the reactivity of large numbers of active pharmaceutical ingredients (APIs). A Takeda Fellowship will support his current project to: (1) develop open-source software for high-throughput quantum chemistry calculations, focusing on the reactivity of drug-like molecules, and (2) develop deep learning models that can quantitatively predict the oxidative stability of APIs. The tools and insights resulting from Wu’s research could help to transform and accelerate the drug-discovery process, offering significant benefits to the pharmaceutical and medical fields and to patients.

      Soojung Yang

      Soojung Yang is a PhD candidate in the Department of Materials Science and Engineering. Yang’s research applies cutting-edge methods in geometric deep learning and generative modeling, along with atomistic simulations, to better understand and model protein dynamics. Specifically, Yang is developing novel tools in generative AI to explore protein conformational landscapes that offer greater speed and detail than physics-based simulations at a substantially lower cost. With the support of a Takeda Fellowship, she will build upon her successful work on the reverse transformation of coarse-grained proteins to the all-atom resolution, aiming to build machine-learning models that bridge multiple size scales of protein conformation diversity (all-atom, residue-level, and domain-level). Yang’s research holds the potential to provide a powerful and widely applicable new tool for researchers who seek to understand the complex protein functions at work in human diseases and to design drugs to treat and cure those diseases.

      Yuzhe Yang

      Yuzhe Yang is a PhD candidate in the Department of Electrical Engineering and Computer Science. Yang’s research interests lie at the intersection of machine learning and health care. In his past and current work, Yang has developed and applied innovative machine-learning models that address key challenges in disease diagnosis and tracking. His many notable achievements include the creation of one of the first machine learning-based solutions using nocturnal breathing signals to detect Parkinson’s disease (PD), estimate disease severity, and track PD progression. With the support of a Takeda Fellowship, Yang will expand this promising work to develop an AI-based diagnosis model for Alzheimer’s disease (AD) using sleep-breathing data that is significantly more reliable, flexible, and economical than current diagnostic tools. This passive, in-home, contactless monitoring system — resembling a simple home Wi-Fi router — will also enable remote disease assessment and continuous progression tracking. Yang’s groundbreaking work has the potential to advance the diagnosis and treatment of prevalent diseases like PD and AD, and it offers exciting possibilities for addressing many health challenges with reliable, affordable machine-learning tools.  More

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      in Data Management & Statistics

      MIT welcomes nine MLK Visiting Professors and Scholars for 2023-24

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      Established in 1990, the MLK Visiting Professors and Scholars Program at MIT welcomes outstanding scholars to the Institute for visiting appointments. MIT aspires to attract candidates who are, in the words of Martin Luther King Jr., “trailblazers in human, academic, scientific and religious freedom.” The program honors King’s life and legacy by expanding and extending the reach of our community. 

      The MLK Scholars Program has welcomed more than 140 professors, practitioners, and professionals at the forefront of their respective fields to MIT. They contribute to the growth and enrichment of the community through their interactions with students, staff, and faculty. They pay tribute to Martin Luther King Jr.’s life and legacy of service and social justice, and they embody MIT’s values: excellence and curiosity, openness and respect, and belonging and community.  

      Each new cohort of scholars actively participates in community engagement and supports MIT’s mission of “advancing knowledge and educating students in science, technology, and other areas of scholarship that will best serve the nation and the world in the 21st century.” 

      The 2023-2024 MLK Scholars:

      Tawanna Dillahunt is an associate professor at the University of Michigan’s School of Information with a joint appointment in their electrical engineering and computer science department. She is joining MIT at the end of a one-year visiting appointment as a Harvard Radcliffe Fellow. Her faculty hosts at the Institute are Catherine D’Ignazio in the Department of Urban Studies and Planning and Fotini Christia in the Institute for Data, Systems, and Society (IDSS). Dillahunt’s research focuses on equitable and inclusive computing. During her appointment, she will host a podcast to explore ethical and socially responsible ways to engage with communities, with a special emphasis on technology. 

      Kwabena Donkor is an assistant professor of marketing at Stanford Graduate School of Business; he is hosted by Dean Eckles, an associate professor of marketing at MIT Sloan School of Management. Donkor’s work bridges economics, psychology, and marketing. His scholarship combines insights from behavioral economics with data and field experiments to study social norms, identity, and how these constructs interact with policy in the marketplace.

      Denise Frazier joins MIT from Tulane University, where she is an assistant director in the New Orleans Center for the Gulf South. She is a researcher and performer and brings a unique interdisciplinary approach to her work at the intersection of cultural studies, environmental justice, and music. Frazier is hosted by Christine Ortiz, the Morris Cohen Professor in the Department of Materials Science and Engineering. 

      Wasalu Jaco, an accomplished performer and artist, is renewing his appointment at MIT for a second year; he is hosted jointly by Nick Montfort, a professor of digital media in the Comparative Media Studies Program/Writing, and Mary Fuller, a professor in the Literature Section and the current chair of the MIT faculty. In his second year, Jaco will work on Cyber/Cypher Rapper, a research project to develop a computational system that participates in responsive and improvisational rap.

      Morgane Konig first joined the Center for Theoretical Physics at MIT in December 2021 as a postdoc. Now a member of the 2023–24 MLK Visiting Scholars Program cohort, she will deepen her ties with scholars and research groups working in cosmology, primarily on early-universe inflation and late-universe signatures that could enable the scientific community to learn more about the mysterious nature of dark matter and dark energy. Her faculty hosts are David Kaiser, the Germeshausen Professor of the History of Science and professor of physics, and Alan Guth, the Victor F. Weisskopf Professor of Physics, both from the Department of Physics.

      The former minister of culture for Colombia and a transformational leader dedicated to environmental protection, Angelica Mayolo-Obregon joins MIT from Buenaventura, Colombia. During her time at MIT, she will serve as an advisor and guest speaker, and help MIT facilitate gatherings of environmental leaders committed to addressing climate action and conserving biodiversity across the Americas, with a special emphasis on Afro-descendant communities. Mayolo-Obregon is hosted by John Fernandez, a professor of building technology in the Department of Architecture and director of MIT’s Environmental Solutions Initiative, and by J. Phillip Thompson, an associate professor in the Department of Urban Studies and Planning (and a former MLK Scholar).

      Jean-Luc Pierite is a member of the Tunica-Biloxi Tribe of Louisiana and the president of the board of directors of North American Indian Center of Boston. While at MIT, Pierite will build connections between MIT and the local Indigenous communities. His research focuses on enhancing climate resilience planning by infusing Indigenous knowledge and ecological practices into scientific and other disciplines. His faculty host is Janelle Knox-Hayes, the Lister Brothers Professor of Economic Geography and Planning in the Department of Urban Studies and Planning.

      Christine Taylor-Butler ’81 is a children’s book author who has written over 90 books; she is hosted by Graham Jones, an associate professor of anthropology. An advocate for literacy and STEAM education in underserved urban and rural schools, Taylor-Butler will partner with community organizations in the Boston area. She is also completing the fourth installment of her middle-grade series, “The Lost Tribe.” These books follow a team of five kids as they use science and technology to crack codes and solve mysteries.

      Angelino Viceisza, a professor of economics at Spelman College, joins MIT Sloan as an MLK Visiting Professor and the Phyllis Wallace Visiting Professor; he is hosted by Robert Gibbons, Sloan Distinguished Professor of Management, and Ray Reagans, Alfred P. Sloan Professor of Management, professor of organization studies, and associate dean for diversity, equity, and inclusion at MIT Sloan. Viceisza has strong, ongoing connections with MIT. His research focuses on remittances, retirement, and household finance in low-income countries and is relevant to public finance and financial economics, as well as the development and organizational economics communities at MIT. 

      Javit Drake, Moriba Jah, and Louis Massiah, members of last year’s cohort of MLK Scholars, will remain at MIT through the end of 2023.

      There are multiple opportunities throughout the year to meet our MLK Visiting Scholars and learn more about their research projects and their social impact. 

      For more information about the MLK Visiting Professors and Scholars Program and upcoming events, visit the website. More

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      Meet the 2023-24 Accenture Fellows

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      The MIT and Accenture Convergence Initiative for Industry and Technology has selected five new research fellows for 2023-24. Now in its third year, the initiative underscores the ways in which industry and research can collaborate to spur technological innovation.

      Through its partnership with the School of Engineering, Accenture provides five annual fellowships awarded to graduate students with the aim of generating powerful new insights on the convergence of business and technology with the potential to transform society. The 2023-24 fellows will conduct research in areas including artificial intelligence, sustainability, and robotics.

      The 2023-24 Accenture Fellows are:

      Yiyue Luo

      Yiyue Luo is a PhD candidate who is developing innovative integrations of tactile sensing and haptics, interactive sensing and AI, digital fabrication, and smart wearables. Her work takes advantage of recent advances in digital manufacturing and AI, and the convergence in advanced sensing and actuation mechanisms, scalable digital manufacturing, and emerging computational techniques, with the goal of creating novel sensing and actuation devices that revolutionize interactions between people and their environments. In past projects, Luo has developed tactile sensing apparel including socks, gloves, and vests, as well as a workflow for computationally designing and digitally fabricating soft textiles-based pneumatic actuators. With the support of an Accenture Fellowship, she will advance her work of combining sensing and actuating devices and explore the development of haptic devices that simulate tactile cues captured by tactile sensors. Her ultimate aim is to build a scalable, textile-based, closed-loop human-machine interface. Luo’s research holds exciting potential to advance ground-breaking applications for smart textiles, health care, artificial and virtual reality, human-machine interactions, and robotics.

      Zanele Munyikwa is a PhD candidate whose research explores foundation models, a class of models that forms the basis of transformative general-purpose technologies (GPTs) such as GPT4. An Accenture Fellowship will enable Munyikwa to conduct research aimed at illuminating the current and potential impact of foundation models (including large language models) on work and tasks common to “high-skilled” knowledge workers in industries such as marketing, legal services, and medicine, in which foundation models are expected to have significant economic and social impacts. A primary goal of her project is to observe the impact of AI augmentation on tasks like copywriting and long-form writing. A second aim is to explore two primary ways that foundation models are driving the convergence of creative and technological industries, namely: reducing the cost of content generation and enabling the development of tools and platforms for education and training. Munyikwa’s work has important implications for the use of foundation models in many fields, from health care and education to legal services, business, and technology.

      Michelle Vaccaro is a PhD candidate in social engineering systems whose research explores human-AI collaboration with the goals of developing a deeper understanding of AI-based technologies (including ChatGPT and DALL-E), evaluating their performance and evolution, and steering their development toward societally beneficial applications, like climate change mitigation. An Accenture Fellowship will support Vaccaro’s current work toward two key objectives: identifying synergies between humans and AI-based software to help design human-AI systems that address persistent problems better than existing approaches; and investigating applications of human-AI collaboration for forecasting technological change, specifically for renewable energy technologies. By integrating the historically distinct domains of AI, systems engineering, and cognitive science with a wide range of industries, technical fields, and social applications, Vaccaro’s work has the potential to advance individual and collective productivity and creativity in all these areas.

      Chonghuan Wang is a PhD candidate in computational science and engineering whose research employs statistical learning, econometrics theory, and experimental design to create efficient, reliable, and sustainable field experiments in various domains. In his current work, Wang is applying statistical learning techniques such as online learning and bandit theory to test the effectiveness of new treatments, vaccinations, and health care interventions. With the support of an Accenture Fellowship, he will design experiments with the specific aim of understanding the trade-off between the loss of a patient’s welfare and the accuracy of estimating the treatment effect. The results of this research could help to save lives and contain disease outbreaks during pandemics like Covid-19. The benefits of enhanced experiment design and the collection of high-quality data extend well beyond health care; for example, these tools could help businesses optimize user engagement, test pricing impacts, and increase the usage of platforms and services. Wang’s research holds exciting potential to harness statistical learning, econometrics theory, and experimental design in support of strong businesses and the greater social good.

      Aaron Michael West Jr. is a PhD candidate whose research seeks to enhance our knowledge of human motor control and robotics. His work aims to advance rehabilitation technologies and prosthetic devices, as well as improve robot dexterity. His previous work has yielded valuable insights into the human ability to extract information solely from visual displays. Specifically, he demonstrated humans’ ability to estimate stiffness based solely on the visual observation of motion. These insights could advance the development of software applications with the same capability (e.g., using machine learning methods applied to video data) and may enable roboticists to develop enhanced motion control such that a robot’s intention is perceivable by humans. An Accenture Fellowship will enable West to continue this work, as well as new investigations into the functionality of the human hand to aid in the design of a prosthetic hand that better replicates human dexterity. By advancing understandings of human bio- and neuro-mechanics, West’s work has the potential to support major advances in robotics and rehabilitation technologies, with profound impacts on human health and well-being. More