In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized (subject to certain rules and regulations).

csail
32 Vassar St, Cambridge
Cambridge, Massachusetts, 02139
United States

Alay Shah

I'm a 19 year old who's been studying the human brain for 6 years. The bulk of my work focuses on investigating new biomarkers in an effort to understand complex elements of human cognition and brain health. My most recent published work explored using eye-tracking technology as a gateway into neurological disorders such as Parkinson's, Dementia, and Multiple Sclerosis, featured in the Human Brain Project. Now, I'm working on translating cutting-edge research into tools that enable a new era of personal brain health built for consumers.

Alexander Amini

Alexander Amini is a postdoctoral researcher at the Massachusetts Institute of Technology (MIT), in the Computer Science and Artificial Intelligence Laboratory (CSAIL) as well as the Founder and Chief Scientist of ThemisAI. Amini's research focuses on building advanced algorithms for safe and trustworthy artificial intelligence (AI). His inventions have been deployed on autonomous vehicles and across domains that require AI to make responsible and reliable decisions. His research has been awarded the prestigious NSF Research Fellowship; includes 40 peer-reviewed publications from top-tier AI venues such as Nature Machine Intelligence, AAAI, NeurIPS, ICML, ICLR, ICRA, and IROS; and has been translated into 7 utility patents. Amini’s inventions have served as the foundation of ThemisAI, which Amini co-founded as a PhD student at MIT to enable the world to create, advance, and deploy trustworthy AI solutions into reality. Additionally, Amini is the lead organizer and lecturer for MIT 6.S191: Introduction to Deep Learning, MIT's introductory course on deep learning -- with over 30,000 globally registered students in 2022 alone, and millions of online lecture views.

Aspen Hopkins

Aspen Hopkins is an MIT Ph.D. student in the Madry Lab and the Center for Deployable Machine Learning. In addition to collaborations with Tableau, Aspen has conducted research on machine learning and data visualization at Apple, NASA Jet Propulsion Labs, and the Scientific Imaging and Computing Institute. From “spell check” techniques for misleading graphs to interventions for fair machine learning pipelines, her research is creating new ways to expose obfuscated facets of data and models. "

Edward Adelson

Edward Adelson is the John and Dorothy Professor of Vision Science in the Department of Brain and Cognitive Sciences and the Computer Science and AI Lab (CSAIL) at MIT. Formerly a vision scientist, he now works on artificial touch sensing for robots. He is a member of the National Academy of Sciences.

George Morgan

George is an engineer with experience in the fields of computer vision and machine learning. He has industry experience deploying systems at scale at companies including Meta, Apple, and most recently Tesla where he made significant contributions to their self-driving software. George left Tesla in July to start Symbolica, an AI company that is using algebraic topology and term rewriting to develop a new learning algorithm that is much more data efficient and opens the door to solving longstanding challenges in deep learning such as causal reasoning, memory, and online learning.

James DiCarlo

James DiCarlo is the Peter de Florez Professor of Neuroscience in the Department of Brain and Cognitive Science at MIT and director of the MIT Quest for Intelligence, and is a principal investigator at the McGovern Institute for Brain Research. His research focuses on using computational methods to understand the brain’s visual system, and with this knowledge, developing brain-machine interfaces to restore or augment lost senses. DiCarlo has received an Alfred P. Sloan fellowship, a Pew Scholar Award, and a McKnight Scholar Award. He earned a PhD in biomedical engineering, and an MD, from Johns Hopkins University.

Keith Murray

Keith Murray is a graduate student at MIT pursuing his Master’s of Engineering in Computation and Cognition. For his undergraduate, also at MIT, he majored in Computation and Cognition, and Linguistics and Philosophy. He’s always been fascinated by questions at the heart of cognitive science.

Luke Igel

"Luke Igel is an undergraduate at MIT studying computer science (S.B.). He has worked as a machine learning researcher and software engineer at SpaceX, NASA JPL, Slack, and multiple startups. He has been published in ICRA for his work in deep reinforcement learning on the Mars Perseverance rover's self-driving system through the Robotic Surface Mobility group at NASA JPL. He also worked on activity planning for SpaceX's Starlink satellite mega-constellation, which is now running his code in low earth orbit. Alongside Wesley Block, he recently completed a feature-length documentary on the history of MIT, a 2-year project that spans 80 years of the Institute's and America's history via AI-enhanced archival footage. He is currently the co-founder of the startup Kino AI, which speeds up video production for both professionals and amateurs via AI-based tools. Keith Murray is a graduate student at MIT pursuing his Master’s of Engineering in Computation and Cognition. For his undergraduate, also at MIT, he majored in Computation and Cognition, and Linguistics and Philosophy. He’s always been fascinated by questions at the heart of cognitive science. He’s worked as a computational neuroscientist at the McGovern Institute, Allen Institute, and CSAIL. His previous work has included training mice to complete navigation tasks in virtual reality to modeling the retina with deep learning. He has been published in the Journal of Computational Biology for his work. He hopes to pursue a PhD in Neuroscience in the near future and envisions himself never leaving the world of academia. "

Patrick Dykstra

"Patrick Dykstra is the co-star of the semi-biographical feature film ‘Patrick and the Whale’ which chronicle’s Patrick’s decade long connection with a family of sperm whales. The film won the Audience Choice Award at the Innsbruck Film Festival, Newport Beach Film Festival, Graz Film Festival and was nominated for both a Panda award (Wildscreen) and Jackson Wild Media Award as well as the Golden Eye award (Zurich Film Festival). Patrick also hosted and filmed the series Chasing Ocean Giants (Discovery Channel) that has aired in over 150 countries. The eight-part series follows Patrick’s journey across the globe to assist some of the world’s leading scientists in discovering mysteries of the ocean. During the production the team filmed numerous world-firsts and provided a valuable platform for the scientists with whom they worked. Patrick won a BAFTA for his cinematography work on the BBC’s Blue Planet 2 and has since filmed nature programs for Netflix, National Geographic, AppleTV+, Discovery, BBC and others. Prior to his work in natural history, Patrick spent eight years as a corporate lawyer working at one of the world’s most prestigious international law firms representing some of the world’s largest companies and was based in New York, Los Angeles and Dubai before leaving the corporate life behind to pursue his passions. Since leaving the corporate world Patrick has visited 102 countries and has filmed in some of the harshest environments including Yemen’s tribal areas, diving under Antarctic ice and at the top of Congo’s erupting volcanos. He is a certified rebreather scuba diver, wingsuit skydiver, hang-glider and para-glider pilot and is passionate about wildlife conservation. When not on the road Patrick is at home in Bristol, UK. "

Pulkit Agrawal

Dr. Pulkit Agrawal is Steven and Renee Finn Chair Assistant Professor in the Department of Electrical Engineering and Computer Science at MIT. He earned his Ph.D. from UC Berkeley and co-founded SafelyYou Inc. His research interests span robotics, deep learning, computer vision, and reinforcement learning. Pulkit completed his bachelor's from IIT Kanpur and was awarded the Directors Gold Medal. His work received the Best Paper Award at Conference on Robot Learning 2021 and Best Student Paper Award at Conference on Computer Supported Collaborative Learning 2011. He is a recipient of Sony Faculty Research Award, Salesforce Research Award, Amazon Research Award, Signatures Fellow Award, Fulbright Science and Technology Award, Goldman Sachs Global Leadership Award, etc. His work has appeared multiple times in MIT Tech Review, Quanta, New Scientist, NYPost, etc.

Ramin Hasani

Ramin Hasani is a Principal AI and Machine Learning Scientist at the Vanguard Group and a Research Affiliate at CSAIL MIT. Ramin’s research focuses on robust deep learning and decision-making in complex dynamical systems. Previously he was a Postdoctoral Associate at CSAIL MIT, leading research on modeling intelligence and sequential decision-making, with Prof. Daniela Rus. He received his Ph.D. degree with distinction in Computer Science at Vienna University of Technology (TU Wien), Austria (May 2020). His Ph.D. dissertation and continued research on Liquid Neural Networks got recognized internationally with numerous nominations and awards such as TÜV Austria Dissertation Award nomination in 2020, and HPC Innovation Excellence Award in 2022. He has also been a frequent TEDx Speaker.

Robert Ajemian

Robert Ajemian graduated with a degree in physics from Harvard, before enrolling at Boston University’s Department of Cognitive and Neural Systems, where he graduated with a PhD specializing in neural networks and computational models for motor control. Currently, he is a research scientist at MIT in the McGovern Institute for Brain Research where he investigates questions in theoretical neuroscience with a focus on neural network models of motor control and memory. His work has been published in scientific journals such as Neuron, Nature, and the Proceedings for the National Academy of Sciences, and his research – particularly with regard to theories of associative memory and mnemonics – have been reported on by news organizations such as CNN, WBUR, Der Spiegel, and the Boston Globe.

Shari Liu

Shari Liu studies how our minds and brains reason about the physical and social world, using the tools of developmental psychology and cognitive neuroscience. She obtained her PhD from Harvard University in 2020, and is currently a postdoctoral fellow at MIT. She is the recipient of the Goethals Teaching Prize (2019) from Harvard University, and the Glushko Dissertation Prize (2021) from the Cognitive Science Society. Starting in July 2023, she will launch her own lab at Johns Hopkins University.

The Chorallaries of MIT

We are MIT’s first mixed-voice a cappella group, founded in 1976. We perform in the Boston/Cambridge area, tour the country, and go on retreat in Vermont (when we aren't in the middle of a pandemic that is). We also perform at the International Championship of Collegiate A Cappella (ICCA) competition. We focus on sound, musicality and performance, and we have a great time singing together!

Vikash Mansinghka

" Vikash Mansinghka is a Principal Research Scientist at MIT, where he leads the Probabilistic Computing Project, part of MIT's CSAIL, Department of Brain & Cognitive Sciences, and the Quest for Intelligence. Vikash holds S.B. degrees in Mathematics and in Computer Science from MIT, as well as an M.Eng. in Computer Science and a PhD in Computation. He also held graduate fellowships from the National Science Foundation and MIT’s Lincoln Laboratory. His PhD dissertation on natively probabilistic computation won the MIT George M. Sprowls dissertation award in computer science, and his research on the Picture probabilistic programming language won an award at CVPR. He co-founded three VC-backed startups: Prior Knowledge (acquired by Salesforce in 2012) and Empirical Systems (acquired by Tableau in 2018), and Common Sense Machines (funded in 2020), and advises in companies such as DeepMind, Intel, and Google. He served on DARPA’s Information Science and Technology advisory board from 2010-2012, currently serves on the editorial board for the Journal of Machine Learning Research, and co-founded the International Conference on Probabilistic Programming."

Yulin Du

I am a fourth-year PhD student at MIT EECS, advised by Prof. Leslie Kaelbling, Prof. Tomas Lozano-Perez and Prof. Joshua B. Tenenbaum. Previously, I obtained my bachelor's degree from MIT, was a research fellow at OpenAI, an intern at Deepmind and FAIR, and got a gold medal at the International Biology Olympiad. I am interested in constructing machine learning tools that enable the development of autonomous embodied agents. In the embodied setting, the world is both highly uncertain and richly combinatorical in nature. To address these challenges, my recent research uses the tools of energy-based models to accurately generatively model the uncertainty in the world and as a tool to construct composable models which may be rapidly adapted to new experiences. My research further uses the underlying energy optimization procedure as an adjustable computational budget, enabling the use of longer computation times to adapt to novel out-of-distribution experiences. Furthermore, embodied learning is richly multimodal in nature, and we need models which universally capture structure across modalities such as vision, text, sound and touch. I am interested in leveraging neural fields as a generic way to discover and capture such rich structure in the world. Finally I'm interested in broader applications of these tools to other domains such as computational biology.