Expanding the Precision of Modern Therapeutics
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Breakthroughs in biology, engineering, and computation continue to redefine what is possible in human health. Building on the momentum of prior MIT ILP Health Science Forums, which highlighted advances in drug discovery, AI-enabled biomolecular modeling, next-generation diagnostics, and precision biomanufacturing, the 2026 MIT Health Science & Technology Forum will spotlight emerging research in diagnosis, brain science, microbial therapeutics, and targeted drug delivery.
This year’s program brings together leading MIT faculty working at the forefront of early detection, brain circuitry and neurodegeneration, the microbiome’s role in health and disease, and new therapeutic approaches that reach previously inaccessible tissues. Complementing the faculty program, MIT-connected startups will deliver rapid-fire presentations showcasing commercialization-ready innovations across diagnostics, delivery systems, computational biology, and health-enabling technologies.
Together, these sessions present a convergent vision for healthcare, one in which earlier detection, deeper biological insight, and engineered delivery platforms expand the reach, precision, and impact of modern therapeutics.
Designed for industry leaders, researchers, and innovators, the 2026 Forum offers a unique opportunity to connect with MIT experts and explore cross-disciplinary advances shaping the future of human health.
Registration Fee ILP Member: Complimentary General Public: $500 for in-person/ $250 for livestream MIT Faculty, Staff, and Students: Limited complimentary in-person seats available
Visiting MIT: https://www.mit.edu/visitmit/ Where to Stay: https://institute-events.mit.edu/visit/where-to-stay Registration Questions: ocrevents@mit.edu
The agenda below is subject to change without prior notice.
Hermann L.F. von Helmholtz Career Development Professor, MIT Associate Professor, MIT Civil and Environmental Engineering Associate Professor, Institute for Medical Engineering and Science
Tami trained in molecular biology and mathematics at Northwestern University, where she conducted research in the laboratory of Jon Widom and was funded by a Barry M. Goldwater Scholarship. She then earned a PhD in Systems Biology from Harvard University, where she conducted research in Roy Kishony’s laboratory. During her graduate research, Tami developed new genomic approaches for understanding how bacteria evolve during infections of individual people. As a postdoc in Eric Alm’s lab at MIT, she further developed and applied these genomic approaches to understand the microbes that colonize us during health.
Tami joined the MIT faculty in January 2018, where she now leads a computational and experimental research group focused on within-person evolution in the skin microbiome, with projects spanning from theoretical population genetics to applied probiotics for the treatment of skin diseases. A major thrust of her lab is uncovering the mechanisms of colonization to enable precision microbiome therapies. She is the recipient of a 2020 NIH New Innovator Award.
Microbiome-based therapies for the skin and other body sites are a promising modality for treating disease and promoting wellness. However, a major challenge to realizing this potential is that most applied bacteria—even those taken from the same body site in healthy humans—do not remain or 'engraft' after application. In this talk, I will discuss how tracking evolution and ecology, along with the appropriate genomic and spatial resolutions, can help us design therapies with a higher chance of engraftment. I will present insights from Cutibacterium acnes and Staphylococcus epidermidis, which together comprise over 75% of the healthy facial skin microbiome and are both being actively explored as probiotics by industry.
Assistant Professor, MIT Media Lab Assistant Professor, MIT Department of Electrical Engineering and Computer Science
Paul Liang is an Assistant Professor at the MIT Media Lab and the Department of Electrical Engineering and Computer Science. He is the founding director of the Multisensory Intelligence research group, which studies the foundations of multisensory artificial intelligence to create human-AI symbiosis across scales and sensory mediums, enhancing productivity, creativity, and well-being.
Paul received his PhD in Machine Learning at Carnegie Mellon University, advised by Louis-Philippe Morency and Ruslan Salakhutdinov, and was a visiting researcher at the Simons Institute at UC Berkeley in the summer of 2024. During his PhD, he also spent time at the research labs of DeepMind, Facebook, Nvidia, and Google. Previously, he received an MS in Machine Learning and a BS with University Honors in Computer Science and Neural Computation from CMU.
Paul's research builds the theoretical foundations, large-scale resources, and neural network architectures to learn from multisensory data. These approaches are widely used to train and evaluate today's multimodal generative AI models used throughout academia and industry. In collaboration with practitioners, he has deployed these systems for problems in mental health, cancer prognosis, and robot control. His research has been recognized by the Siebel Scholars Award, Waibel Presidential Fellowship, Facebook PhD Fellowship, Center for ML and Health Fellowship, Rising Stars in Data Science, and four best paper awards at international conferences and workshops. Outside of research, Paul received the Alan J. Perlis Graduate Student Teaching Award for designing a new pedagogy for multimodal AI.
Building multisensory AI systems that learn from multiple sensory inputs such as text, speech, video, real-world sensors, wearable devices, and medical data holds great promise for impact in supporting human health and well-being. This talk will cover our recent work on large-scale multimodal clinical benchmarks, with a million patient samples distributed across imaging, 3D/video, temporal sensing, graphs, and multimodal data. Using CLIMB, we trained QoQ-Med, the first and most powerful open-source foundation model for clinical reasoning across medical images, time-series signals, and text reports. These models enable strong reasoning and diagnosis capabilities to assist clinicians in their workflows.
James W. (1963) and Patricia T. Poitras Professor, Brain and Cognitive Sciences, MIT Associate Director, McGovern Institute Director, Hock E. Tan and K. Lisa Yang Center for Autism Research Director, Model Systems and Neurobiology, Stanley Center for Psychiatric Research Institute Member, Broad Institute of MIT and Harvard
Guoping Feng joined the McGovern Institute in 2010 and current serves as its associate director. He is a faculty member in the brain and cognitive sciences department, where he holds the James W. (1963) and Patricia T. Poitras Professorship. Feng is also the director of the Hock E. Tan and K. Lisa Yang Center for Autism Research at MIT, as well as director of model systems and neurobiology in the Stanley Center for Psychiatric Research at the Broad Institute.
Originally from Zhejiang Province in China, Guoping Feng studied medicine at Zhejiang University School of Medicine. He obtained his PhD from the State University of New York at Buffalo in the laboratory of Linda Hall and postdoctoral training at Washington University in St. Louis under the guidance of Joshua Sanes. Prior to joining the faculty at MIT in 2010, he was a faculty member in the neurobiology department at Duke University School of Medicine.
RareNet is built around a global, collaborative consortium of neuroscientists, clinicians, patient advocates, and industry partners that connects fragmented research efforts, expands access to patient data and samples, and fosters trust and shared goals. Central to its mission is a therapeutic pipeline accelerator that reduces early research risk, strengthens safety and reliability, and speeds translation from discovery to clinical and commercial readiness. Led by faculty director Guoping Feng, RareNet integrates MIT expertise with advanced tools such as disease modeling and artificial intelligence to extract insights from biological and clinical datasets, enabling a deeper understanding of complex and rare brain conditions and generating insights with broad relevance across uncommon neurological disorders.
You may cancel your registration for a full refund through May 4. Refunds will be issued to the original form of payment. From May 4 to May 11, partial refunds will be available, minus a service fee ($50 for in-person registrations and $25 for virtual). No refunds will be issued after May 11. To cancel, please email ocrevents@mit.edu.