MIT
x = independently organized TED event

This event occurred on
December 4, 2021
Cambridge, Massachusetts
United States

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).

MIT Stata Center
MIT CSAIL, 32 Vassar Street
Cambridge, Massachusetts, 02139
United States
Event type:
University (What is this?)
See more ­T­E­Dx­M­I­T events

Speakers

Speakers may not be confirmed. Check event website for more information.

Aleksander Madry

Aleksander Madry is the Cadence Design Systems Professor of Computing in the MIT EECS Department and a member of CSAIL. He received his Ph.D. from MIT in 2011. Prior to joining the MIT's faculty, he spent a year as a postdoctoral researcher at Microsoft Research New England and then he was on the faculty of EPFL until early 2015. He is the Director of the MIT Center for Deployable Machine Learning and a Faculty Co-Lead of the MIT AI Policy Forum. His research interests spans machine learning, optimization and algorithmic graph theory. In particular, he has a strong interest in building on the existing machine learning techniques to forge a decision-making toolkit that is reliable and well-understood enough to be safely and responsibly deployed in the real world.

Cathy Wu

Cathy Wu works at the intersection of machine learning, optimization, and large-scale urban systems and other societal systems. Her recent research focuses on mixed autonomy systems in mobility, which studies the complex integration of automation such as self-driving cars into existing urban systems. She is broadly interested in developing principled computational tools to enable reliable and complex decision-making for critical societal systems. She received her B.S. and M.Eng in EECS at MIT in 2012 and 2013, and a Ph.D. in EECS at UC Berkeley in 2018. She has received numerous fellowship, best paper, and teaching awards. Throughout her career, Cathy has collaborated and worked broadly across fields, including transportation, computer science, electrical engineering, mechanical engineering, urban planning, and public policy, and institutions, including Microsoft Research, OpenAI, the Google X Self-Driving Car Team, AT&T, Caltrans, Facebook, and Dropbox. As the founder and Chair of the Interdisciplinary Research Initiative within the ACM Future of Computing Academy, she is actively building international programs to unlock the potential of interdisciplinary research in computing.

Jinhua Zhao

Prof. Jinhua Zhao integrates behavioral and computational thinking to decarbonize the global mobility system. He shapes sustainable travel behavior and designs multimodal mobility system. He runs the JTL Urban Mobility Lab and Transit Lab at MIT and leads long-term research programs with transportation authorities and operators in London, Chicago, Washington D.C., Singapore and Hong Kong. Prof. Zhao sees transportation as a language to describe a person, characterize a city, and understand an institution, and enables cross-culture learning between cities in North America, Asia and Europe. He is the co-founder and chief scientist for TRAM, a mobility decarbonization venture. He founded and directs the MIT Mobility Initiative. Link: web.mit.edu/jinhua/www

Manolis Kellis

Manolis Kellis is a professor of computer science at MIT, a member of the Broad Institute of MIT and Harvard, a principal investigator of the Computer Science and Artificial Intelligence Lab at MIT, and head of the MIT Computational Biology Group (compbio.mit.edu). His research spans disease circuitry, genetics, genomics, epigenomics, regulatory genomics, and comparative genomics, applied to Alzheimer's Disease, Obesity, Schizophrenia, Cardiac Disorders, Cancerand , Immune Disorders. He has led several large-scale genomics projects, authored over 250 journal publications cited more than 125,000 times, and led more than 20 multi-year grants from the NIH. He received the US Presidential Early Career Award in Science and Engineering by US President Barack Obama, the Mendel Medal, and the NIH Director’s Transformative Research Award.

Marzyeh Ghassemi

Dr. Marzyeh Ghassemi is an Assistant Professor at MIT in Electrical Engineering and Computer Science (EECS) and Institute for Medical Engineering & Science (IMES), and a Vector Institute faculty member holding a Canadian CIFAR AI Chair and Canada Research Chair. She holds a Herman L. F. von Helmholtz Career Development Professorship, and was also named one of MIT Tech Review’s 35 Innovators Under 35. Previously, she was a Visiting Researcher with Alphabet’s Verily and an Assistant Professor at University of Toronto. Prior to her PhD in Computer Science at MIT, she received an MSc. degree in biomedical engineering from Oxford University as a Marshall Scholar, and B.S. degrees in computer science and electrical engineering as a Goldwater Scholar at New Mexico State University. Professor Ghassemi has a well-established academic track record across computer science and clinical venues, including NeurIPS, KDD, AAAI, MLHC, JAMIA, JMIR, JMLR, AMIA-CRI, EMBC, Nature Medicine, Nature Translational Psychiatry, and Critical Care. Her work has been featured in popular press such as MIT News, NVIDIA, Huffington Post.

Ramesh Raskar

Ramesh Raskar is an Associate Professor at MIT Media Lab and directs the Camera Culture research group. His focus is on Machine Learning and Imaging for health and sustainability. They span research in physical (e.g., sensors, health-tech), digital (e.g., automated and privacy-aware machine learning) and global (e.g., geomaps, autonomous mobility) domains. At MIT, his co-inventions include camera to see around corners, femto-photography, automated machine learning (auto-ML), private ML (split-learning), low-cost eye care devices (Netra,Catra, EyeSelfie), a novel CAT-Scan machine, motion capture (Prakash), long distance barcodes (Bokode), 3D interaction displays (BiDi screen), new theoretical models to augment light fields (ALF) to represent wave phenomena and algebraic rank constraints for 3D displays(HR3D). His work has appeared in NYTimes, CNN, BBC, NewScientist, TechnologyReview and several technology news websites. His invited and keynote talks include TED, Wired, TEDMED, Darpa Wait What, MIT Technology Review, Google SolveForX and several TEDx venues. His co-authored books include Spatial Augmented Reality, Computational Photography, and 3D Imaging (under preparation).

S. Craig Watkins

S. Craig Watkins is the Ernest A. Sharpe Centennial Professor at the University of Texas at Austin and the Founding Director of the Institute for Media Innovation. His research focuses on the impacts of media and data-based systems on human behavior, with a specific concentration on issues related to systemic racism. He is the author of six books and several articles and book chapters examining the intersections between race, technology, and society. His research also considers how diverse communities seek to adopt and deploy technology in innovative ways that address data literacy, civic life, and health. This work has been supported by the MacArthur Foundation. Currently, Watkins is leading a team that will address the issue of artificial intelligence and systemic racism in a new six-year program funded by the Office of Vice President for Research at the University of Texas at Austin. The team will focus on the broad and fundamental scientific challenge of achieving racially equitable AI, while being grounded in testing the applicability of specific methods, models, processes, and procedures in critical domains like health and transportation. A key component of the research is to examine how various stakeholders—developers of technologies, the private and public sectors, and citizens—can work to create a more equitable AI future.

Tian Gu Tian Gu

Tian Gu is a Research Scientist at MIT, where he is the co-Investigator of the Photonic Materials Research Group. His primary research interests involve nano-/micro-optics, integrated photonics, and photonic materials, focusing on the areas of metasurface flat optics, optical phase change materials, data communications, on-chip spectroscopy, photovoltaics, flexible photonics, etc. He is also the co-Founder and President of LyteChip Inc., an MIT spin-off company that develops advanced optics and photonics technologies. He received his B.S. degree from Beijing Institute of Technology in Electrical Engineering, and Ph.D. degree from University of Delaware in Electrical and Computer Engineering. He is a topic chair of IEEE Summer Topicals Meeting on Reconfigurable Optics and Photonics and served on the conference program committees for CLEO, IEEE Photonics Conference, IEEE Optical Interconnects Conference, IEEE SENSORS, International Congress on Glass, International Conference on Concentrator Photovoltaic Systems, etc. He is a recipient of the SPIE Rising Researcher Award, R&D 100 Award, TechConnect National Innovation Award, among others.

Organizing team

John
Werner

Brookline, MA, United States
Organizer

Daniela
Rus

Cambridge, MA, United States
Co-organizer