AI and Web3: Venture Studio

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). In his recent role at Facebook, he launched and led innovation teams in Digital Health, Health-tech, Satellite Imaging, TV and Bluetooth bandwidth for Connectivity, VR/AR and 'Emerging Worlds' initiative for FB. Before MIT, he co-invented techniques for AR, Computational Photography, Shader Lamps (projector-AR), composite RFID (RFIG), multi-flash non-photorealistic camera for depth edge detection, quadric transfer methods for multi-projector curved displays. He received the Lemelson Award 2016 and ACM SIGGRAPH Achievement Award 2017, Technology Review TR100 award 2004 (which recognizes top young innovators under the age of 35), Global Indus Technovator Award (top 20 Indian technology innovators worldwide) 2003, Alfred P. Sloan Research Fellowship award 2009 and Darpa Young Faculty award 2010. Other awards include Marr Prize honorable mention 2009, LAUNCH Health Innovation Award, presented by NASA, USAID, US State Dept+ NIKE, 2010, Vodafone Wireless Innovation Award (first place) 2011. 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). He has worked on special research projects at Google [X], Facebook, Apple and co-founded/advised several startups. He launched REDX.io, a platform for young innovators to explore AI-for-Impact. He frequently consults for dynamic organizations to conduct 'SpotProbing' exercises to spot opportunities and probe solutions.

I am an Assistant Professor in the department of Electrical Engineering and Computer Science (EECS) at MIT. My lab is a part of the Computer Science and Artificial Intelligence Lab (CSAIL), is affiliated with the Laboratory for Information and Decision Systems (LIDS) and involved with NSF AI Institute for Artificial Intelligence and Fundamental Interactions ( IAIFI ). I completed my Ph.D. at UC Berkeley; undergraduate studies from IIT Kanpur. Co-founded SafelyYou Inc. that builds fall prevention technology. Advisor to Tutor Intelligence, Common Sense Machines, and AI Foundry. My overarching research interest is to build machines that can automatically and continuously learn about their environment. The hope is that the end result of such learning will be similar to development of what humans call common sense. I refer to this line of work as "computational sensorimotor learning" and it encompasses computer vision, robotics, reinforcement learning, and other learning based approaches to control. Some of my past work has also touched upon principles of cognitive science, neuroscience to draw upon inspiration from these disciplines.