Understanding current state-of-the-art and anticipating major advances for autonomous systems, either in product development or on the manufacturing floor, is critical for many industries. This conference will offer a unique view into MIT research on tools and infrastructure for autonomous systems, as well as MIT’s vision of the future for this topic.
The conference has three major themes:
* Autonomous vehicles (land, air, and sea)
* Autonomous manufacturing
* Platforms for autonomous systems
Join us to learn how to prepare for the increasing presence of autonomy and how to incorporate it to make your business more competitive, safer, adaptive, and more effective.
This conference will benefit both technologists who want to understand the details and inner workings, advantages, and limitations of autonomy, as well as executives who want to arm themselves to make better strategic decisions.
Join the MIT ILP for a four-part virtual conference on April 8-9 & 15-16 for morning talks and Q&A each day. Daily topics are as follows:
April 8 (Wed) Session 1: Autonomous Vehicles
April 9 (Thu) Session 2: Platform Tech for Autonomy
April 15 (Wed) Session 3: Autonomy Startups with MIT Startup Exchange
April 16 (Thu) Session 4: Autonomous Manufacturing
Irina Sigalovsky works in the Office of Corporate Relations at MIT where she builds mutually beneficial partnerships between corporations and MIT. Dr. Sigalovsky comes to MIT with 10 years of international experience in innovation strategy, technology forecasting and external innovation. Prior to MIT, Irina worked at GEN3 Partners, Inc. as a senior principal collaborating with Fortune 1000 companies to focus their innovation investments, execute strategic innovation agendas, and develop business globally. Throughout her career, Irina has taught at Tufts University, MIT Sloan, X-Prize Lab@MIT, MIT HST, Boston and Harvard Universities.
Sertac Karaman is the Class of '48 Career Development Chair Associate Professor of Aeronautics and Astronautics at the Massachusetts Institute of Technology. He is a member of the Laboratory for Information and Decision Systems and the Institute for Data, Systems and Society. He has obtained B.S. degrees in mechanical engineering and and in computer engineering from the Istanbul Technical University, Turkey, in 2007, an S.M. degree in mechanical engineering from MIT in 2009, and a Ph.D. degree in electrical engineering and computer science also from MIT in 2012. His research interests lie in the broad areas of robotics and control theory. In particular, he studies the applications of probability theory, stochastic processes, stochastic geometry, formal methods, and optimization for the design and analysis of high-performance cyber-physical systems. The application areas include driverless cars, unmanned aerial vehicles, distributed aerial surveillance systems, air traffic control, certification and verification of control systems software, among many others. His research and teaching won numerous awards, including the Army Research Office Young Investigator Program Award in 2015 and the NSF Faculty Career Development (CAREER) Award in 2014.
As the technology for autonomous vehicles matures, the broad reach of the technology comes to focus, together with the new challenges and the shifting opportunities. The car that can drive itself under any condition better than any human driver - the holy-grail of autonomous vehicles - may not be as close as once thought. However, it is becoming clear that other opportunities with tremendous economic and social impact may be well within reach. In fact, fielding autonomous vehicles on the ground, in the air, on the water and even in space may transform a number of existing industries and create new ones. In this talk, we discuss three emerging technologies that will allow autonomous vehicles to interact with humans, rapidly react to their environment, and showcase complex autonomy even in miniature form factors, respectively. We also briefly discuss opportunities in business and in teaching of autonomous vehicles.
Research Scientist, MIT AgeLab
Associate Director, New England University Transportation Center
Bryan Reimer, Ph.D., is a Research Scientist in the MIT Center for Transportation and Logistics, a researcher in the AgeLab, and the Associate Director of The New England University Transportation Center at MIT. Bryan’s research seeks to develop theoretical and applied insight into driver behavior. His work aims to find solutions to the next generation of human factors challenges associated with driver attention management, distraction, automation and the use of advanced driver assistance systems to maximize mobility and safety. His work leverages laboratory experimentation, driving simulation, field testing, and naturalistic driving studies to develop a comprehensive understanding of visual, physiological, behavioral, and overall performance characteristics associated with how drivers respond to the increasing complexity of the modern operating environment. His research is multidisciplinary, drawing together traditional psychological methods with big data analytics in computer vision, deep learning, and predictive modeling. He is an author on over 250 technical contributions in transportation and related human factors areas. His work informs technology development, business strategy, and public policy.
He founded and leads three academic partnerships with industry. The Advanced Human Factors Evaluator for Attentional Demand (AHEAD) consortium, aims to develop the next generation of driver attention measurement tools. The Advanced Vehicle Technology (AVT) consortium, seeks to understand how drivers use emerging, commercially available vehicle technologies including advanced driver assistance systems and automated driving systems. Finally, the Clear Information Presentation (Clear-IP) consortium explores the impact of typography and other design features on usability in glance-based environments such as during driving or while using smartphones.
Dr. Reimer collaborates with industries worldwide on the topics of driver safety, vehicle automation and other technological concerns related to human factors. In addition to his work with students and a multi-disciplinary team at MIT, he is a strategic advisor to Affectiva and an active consultant to the entrepreneurial community. He is a Contributor to Forbes and regularly featured in the press as a mobility futurist and as an expert in automotive safety. A seasoned conference and event presenter, Reimer has provided keynote addresses on the topics of driver attention and vehicle automation. In his 2018 TEDx talk, “There’s more to the safety of driverless cars than AI”, he discusses the undertreated health crisis on our roads and the limits of focusing on automation alone as a solution. He suggests that the modernization and automation of our mobility ecosystem will require increased transparency and collaboration between the public and private sectors to enhance consumer trust and make vehicle automation the most critical life-saving technology of the century.
Dr. Reimer is the 2019 recipient of the Jack A. Kraft Innovator Award from the Human Factors and Ergonomics Society (HFES). He received an inaugural 2018 Autos2050 Impact Award for his innovative contributions to the automotive industry, along with members of Congress, a governor, state senator, two CEOs, and several other leaders deeply concerned with the future of transportation, His academic contributions have been acknowledged through several paper awards including a highly selective 2017 CHI best paper.
His research has been featured in: The Wall Street Journal, The New York Times, USA Today, The Washington Post, Nova, NBC News, Reuters, The Associated Press, Wired, Gizmodo, MIT Technology Review, Discovery Channel, BBC Horizon, Fast Company, The Boston Globe and Science News, among others. A Boston Globe Magazine First Person article “MIT AgeLab scientist Bryan Reimer on the perils of driver distraction” provided his views on automotive safety research. Science Careers featured Dr. Reimer in a Career Profile, “Focus on Aging: Engineering Safer Drivers”. A BBC Horizon documentary, “Surviving a Car Crash,” focused on his work as a key innovation in the future of automotive safety.
His work has been supported by Toyota, Jaguar Land Rover, BMW, Ford Motor Company, Honda, Audi, Subaru R & D, Mazda, Volvo Cars, Veoneer (Autoliv), Aptiv (Delphi), Denso, Panasonic Automotive, Lear, Takata, The Hartford, Liberty Mutual, Progressive, Travelers, Agero, Google, Affectiva, Monotype Imaging, TravelCenters of America, the Santos Family Foundation, the Insurance Institute for Highway Safety, Consumer Reports, JD Power, AAA Foundation for Traffic Safety, Global Automakers, AARP, Johnson & Johnson, Shire Pharmaceuticals, and the United States Department of Transportation.
He is a graduate of the University of Rhode Island with a B.S. in Industrial Engineering, an M.S. in Manufacturing Engineering and a Ph.D. in Industrial and Manufacturing Engineering.
The concept of automating vehicles and removing the driver from direct control of the throttle, brake, and steering wheel was first explored nearly 100 years ago. Over the decades since, automation of various features has gradually infiltrated the automobile. Today, on the heels of the DARPA Urban Challenge and Google’s Self-Driving Car Project, we are closer than ever to realizing aspirations of a century ago, but challenges remain. This talk will center on elements of what is known about automation in the vehicle today and our evolution towards self-driving. Topics will include: observations on the use of Advanced Driver Assistance Systems (ADAS) and production level automated driving features (Autopilot, Pilot Assist, Super Cruise, etc.); the shifting nature of what we do in modern vehicles, challenging what is today’s distraction - secondary tasks or driving; and key points to consider regarding the future of robots on our roads. How might the intersection of artificial intelligence embodied in one the most complex activities humans perform - intersect with society’s demand for economical, efficient and safe mobility? How can human factors insight, psychological research, and policy leadership help to accelerate innovations that will someday change how we live and move? How fast might the automated, electrified future of mobility really take hold?
Assistant Professor, MIT Department of Aeronautics and Astronautics
Luca Carlone is the Charles Stark Draper Assistant Professor in the Department of Aeronautics and Astronautics at the Massachusetts Institute of Technology, and a Principal Investigator in the Laboratory for Information & Decision Systems (LIDS). He received his PhD from the Polytechnic University of Turin in 2012. He joined LIDS as a postdoctoral associate (2015) and later as a Research Scientist (2016), after spending two years as a postdoctoral fellow at the Georgia Institute of Technology (2013-2015). His research interests include nonlinear estimation, numerical and distributed optimization, and probabilistic inference, applied to sensing, perception, and decision-making in single and multi-robot systems. His work includes seminal results on certifiably correct algorithms for localization and mapping, as well as approaches for visual-inertial navigation and distributed mapping. He is a recipient of the 2017 Transactions on Robotics King-Sun Fu Memorial Best Paper Award, the best paper award at WAFR '16, the best Student paper award at the 2018 Symposium on VLSI Circuits, and was best paper finalist at RSS '15.
Robot perception and computer vision have witnessed an unprecedented progress in the last decade. Robots and autonomous vehicles are now able to detect objects, localize them, and create large-scale maps of an unknown environment, which are crucial capabilities for navigation and manipulation. Despite these advances, both researchers and practitioners are well aware of the brittleness of current perception systems, and a large gap still separates robot and human perception. While many applications can afford occasional failures (e.g., AR/VR, domestic robotics), high-integrity autonomous systems (including self-driving vehicles) demand a new generation of algorithms. This talk discusses two efforts targeted at bridging this gap. The first focuses on robustness: I present recent advances in the design of certifiable perception algorithms that are robust to extreme amounts of outliers and afford performance guarantees. These algorithms are “hard to break” and are able to work in regimes where all related techniques fail. The second effort targets high-level understanding. While humans are able to quickly grasp both geometric and semantic aspects of a scene, high-level scene understanding remains a challenge for robotics. I present recent work on real-time metric-semantic understanding, which combines robust estimation with deep learning.
Samuel C Collins Professor of Mechanical and Ocean Engineering
Associate Head for Research, Mechanical Engineering
Co-Director, Ford-MIT Alliance
MIT Department of Mechanical Engineering
John J. Leonard is Samuel C. Collins Professor of Mechanical and Ocean Engineering and Associate Department Head for Research in the MIT Department of Mechanical Engineering. He is also a member of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). His research addresses the problems of navigation and mapping for autonomous mobile robots and underwater vehicles. He holds the degrees of B.S.E.E. in Electrical Engineering and Science from the University of Pennsylvania (1987) and D.Phil. in Engineering Science from the University of Oxford (1994). He was team leader for MIT's DARPA Urban Challenge team, which was one of eleven teams to qualify for the Urban Challenge final event and one of six teams to complete the race. He is the recipient of an NSF Career Award (1998) and the King-Sun Fu Memorial Best Transactions on Robotics Paper Award (2006). He is an IEEE Fellow (2014).
This talk will describe some of the challenges and opportunities in autonomy research today, with a focus on trends and lessons in self-driving research. We will discuss some of the major challenges and research opportunities in self-driving, including building and maintaining high-resolution maps, interacting with humans both inside and outside of vehicles, dealing with adverse weather, and achieving sufficiently high detection with low probabilities of false alarms in challenging settings. We will review the different approaches to automated driving, including SAE Level 2 and SAE Level 4 systems, as well as the Toyota Guardian approach, which flips the conventional mindset from having the human guard the AI (as in SAE Level 2 systems) to instead using AI to guard the human driver. We will discuss research opportunities in mapping, localization, perception, prediction, and planning and control to realize improved safety through advanced automation in the future.
Manager, Corporate Relations
MIT Industrial Liaison Program
Dr. Kenneth A. Goldman joined the MIT Industrial Liaison Program in 1988, managing a diverse portfolio of mostly European memberships, and concentrating in telecommunications and high technology. Before then he worked at Project Athena, MIT's experiment in distributed educational computing, where he organized and managed the visitor and demonstration facility.
Dr. Goldman has special responsibility for relations with the MIT Media Laboratory, the Department of Linguistics and Philosophy, and the Department of Political Science.
Until recently he was manager of the Communications, Information Technology and Financial Services Industry group of Corporate Relations. He speaks fluent Italian, Russian and Serbocroatian, and some French and Spanish. He has studied many other languages. He has travelled extensively throughout both Eastern and Western Europe and lived in Belgrade for several years.
After completing a doctoral degree in Slavic Languages and Literatures, applying information technology to analyze Serbocroatian oral epic, Dr. Goldman worked for several years in the Division of Research at the Harvard Business School, in the Program for Industry and Company Analysis. Following that he worked for Compulex, Inc. of Lowell, MA, which produced multilingual word processing systems, where he was hired as manager of documentation and training, and then assumed responsibility for customer support, product design and product management. He then worked in a number of positions in the software industry before coming to Project Athena.
Cecil H. Green Professor of Electrical Engineering
MIT Department of Electrical Engineering and Computer Science
Muriel Médard is the Cecil H. Green Professor in the EECS Department at MIT and leads the Network Coding and Reliable Communications Group at the Research Laboratory for Electronics. She has co-founded three companies to commercialize network coding. She has served as editor for the Institute of Electrical and Electronics Engineers (IEEE), of which she was elected Fellow, and as Editor in Chief of the IEEE Journal on Selected Areas in Communications. She was President of the IEEE Information Theory Society in 2012, and served on its board of governors for eleven years. She received the 2009 IEEE Communication Society and Information Theory Society Joint Paper Award, the 2009 William R. Bennett Prize, the 2002 IEEE Leon K. Kirchmayer Prize Paper Award, and the 2018 ACM SIGCOMM Test of Time Paper Award. She received the 2016 IEEE Vehicular Technology James Evans Avant Garde Award, the 2017 Aaron Wyner Distinguished Service Award and the 2017 Edwin Howard Armstrong Achievement Award.
5G and future Gs contend with an increasingly dynamic and heterogenous environment, with a multitude of vendors, wireless connectivity standards, requirements, verticals and use cases. The traditional approach inherited from telephony has been one based on careful, deterministic management. We present how such randomness, far from being detrimental, can beneficial when correctly exploited, and show that, surprisingly, random approaches in many cases are actually optimal.
Senior Research Fellow, MIT Communications Futures Program
MIT Computer Science and Artificial Intelligence Laboratory
Dr. William Lehr is a telecommunications and Internet industry economist and consultant with over twenty-five years of experience. He regularly advises senior industry executives and policymakers in the U.S. and abroad on the market, industry, and policy implications of events relevant to the Internet ecosystem. He is a research scientist in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology, currently engaged several multidisciplinary research projects within the Advanced Networking Architecture Group in CSAIL (ANA). Dr. Lehr's research focuses on the economics and regulatory policy of the Internet infrastructure industries. He teaches courses on the economics, business strategy, and public policy issues facing telecommunications, Internet, and eCommerce companies, and is a frequent speaker at international industry and academic conferences. He is the author of numerous publications on such topics as the measurement of economic impacts of Information technologies, the economics of technical standard setting, the pricing of Internet services, and the implications of commercializing novel Internet and wireless technologies for industry structure and regulatory policy.
In addition to his academic research, Dr. Lehr provides litigation, economic, and business strategy consulting services for firms in the information technology industries in the U.S. and abroad. Dr. Lehr has advised information technology companies on strategic marketing, pricing, financial planning, and competitive strategy; and government agencies in the United States and abroad on telecommunications and Internet policy matters. Dr. Lehr has prepared expert witness testimony for both private litigation and for regulatory proceedings before the FCC, before numerous state commissions and for numerous regulatory agencies abroad.
Dr. Lehr holds a PhD in Economics from Stanford (1992), an MBA from the Wharton Graduate School (1985), and MSE (1984), BS (1979) and BA (1979) degrees from the University of Pennsylvania.
The transition to 5G is underway and is realizing the 5G future is viewed by many as essential to sustain national competitiveness and as an essential infrastructure platform for supporting Smart-X, where X may be replaced with healthcare, greener energy grids, transport systems, supply chains, etcetera. But separating the hype from reality is challenging, in part, because 5G is part of a horizon vision that has the potential to significantly alter the fundamental economics that have characterized the evolution of mobile networking through its first four generations. None of today's 5G offerings nor those that will be available in the next few years will deliver the full complement of 5G promised performance improvements, and many analysts are skeptical that those performance improvements are really needed. Key implications of realizing the 5G promise are the need to transition toward more localized and granular control of network resources and increased converged/shared ownership of core resources, but how these may be managed and who will bear responsibility for the investment leaves the implications for the competitive landscape for wireless infrastructure services uncertain. While the incumbent mobile network operators (MNOs) are likely to continue to lead the drive toward 5G, their role in the wireless ecosystem may change significantly. This talk will focus on highlighting an economists' perspective on what 5G, viewed as a horizon vision, may mean for the evolution of wireless broadband networking and the disruptive potential that vision portends.
Professor of Computer Science and Engineering
MIT Department of Electrical Engineering and Computer Science
Samuel Madden is a Professor of Electrical Engineering and Computer Science in MIT's Computer Science and Artificial Intelligence Laboratory and Chief Scientist at Cambridge Mobile Telematics (CMT). His research interests include databases, distributed computing, and networking. Research projects include the C-Store column-oriented database system, the CarTel mobile sensor network system, and the Relational Cloud "database-as-a-service". Madden co-directs the Data Systems and AI Lab (DSAIL), an industry-backed initiative to unite researchers at MIT and leaders from industry to investigate the issues related to building systems that incorporate AI and AI for systems. At CMT, he focuses on helping the company develop technologies to make roads safer by making drivers better.
Madden received his Ph.D. from the University of California at Berkeley in 2003 where he worked on the TinyDB system for data collection from sensor networks. Madden was named one of Technology Review's Top 35 Under 35 in 2005, and is the recipient of several awards, including an NSF CAREER Award in 2004, a Sloan Foundation Fellowship in 2007, best paper awards in VLDB 2004 and 2007, and a best paper award in MobiCom 2006. He also received a a "test of time" award in SIGMOD 2013 (for his work on Acquisitional Query Processing in SIGMOD 2003), and a ten year best paper award in VLDB 2015 (for his work on the C-Store system). He is a founder of several companies, including Vertica Systems, acquired by HP in 2012, and Cambridge Mobile Telematics (CMT).
In this talk, I will review talk about how research we developed at MIT led to the development of Cambridge Mobile Telematics, the leading provider of technology to help measure and improve driving. I’ll talk about how smartphones can provide a dramatic measure of a driver’s crash risk, and how giving users feedback can cause them to improve their behavior. I’ll also review how the recent spread of COVID-19 has changed people’s driving habits.
Assistant Professor of Electrical Engineering and Computer Science
MIT Department of Electrical Engineering and Computer Science
Vivienne Sze received the B.A.Sc. (Hons) degree in electrical engineering from the University of Toronto, Toronto, ON, Canada, in 2004, and the S.M. and Ph.D. degree in electrical engineering from the Massachusetts Institute of Technology (MIT), Cambridge, MA, in 2006 and 2010 respectively. In 2011, she received the Jin-Au Kong Outstanding Doctoral Thesis Prize in Electrical Engineering at MIT.
She has been an Assistant Professor at MIT in the Electrical Engineering and Computer Science Department since August 2013. Her research interests include energy-aware signal processing algorithms, and low-power circuit and system design for portable multimedia applications. Prior to joining MIT, she was a Member of Technical Staff in the Systems and Applications R&D Center at Texas Instruments (TI), Dallas, TX, where she designed low-power algorithms and architectures for video coding. She also represented TI at the international JCT-VC standardization body developing HEVC. Within the committee, she was the primary coordinator of the core experiment on coefficient scanning and coding, and has chaired/vice-chaired several ad hoc groups on entropy coding. She is a co-editor of ÒHigh Efficiency Video Coding (HEVC): Algorithms and Architectures (Springer, 2014).
Prof. Sze is a recipient of the 2016 AFOSR Young Investigator Research Program (YIP) Award, 2016 3M Non-Tenured Faculty Award, 2014 DARPA Young Faculty Award, 2007 DAC/ISSCC Student Design Contest Award and a co-recipient of the 2008 A-SSCC Outstanding Design Award. She received the Natural Sciences and Engineering Research Council of Canada (NSERC) Julie Payette fellowship in 2004, the NSERC Postgraduate Scholarships in 2005 and 2007, and the Texas Instruments Graduate Women's Fellowship for Leadership in Microelectronics in 2008.
Computing near the sensor is preferred over the cloud due to privacy and/or latency concerns for a wide range of applications including robotics/drones, self-driving cars, smart Internet of Things, and portable/wearable electronics. However, at the sensor there are often stringent constraints on energy consumption and cost in addition to the throughput and accuracy requirements of the application. In this talk, we will describe how joint algorithm and hardware design can be used to reduce energy consumption while delivering real-time and robust performance for applications including deep learning, computer vision, autonomous navigation/exploration and video/image processing. We will show how energy-efficient techniques that exploit correlation and sparsity to reduce compute, data movement and storage costs can be applied to various tasks including image classification, depth estimation, super-resolution, localization and mapping.
Program Director, MIT Startup Exchange
Dr. Rebecca Xiong joined Corporate Relations as Program Director, Startup Exchange in October 2018.
Dr. Xiong comes to Corporate Relations with more than 15 years of experience in the MIT Startup Ecosystem, having co-founded and worked at multiple MIT startups. Most recently, as Co-founder and Chief Scientist at SocMetrics, she leads product management, data science, and machine learning for SocMetric’s personalization and marketing campaign products. Before SocMetrics, Xiong co-founded Going.com. Going.com connected people via local events to enhance their offline social life, and through Rebecca’s leadership grew to 1M members, tens of millions of monthly pageviews, and finally its acquisition by AOL. Before these two entrepreneurial endeavors, Xiong held positions as Product Marketing Manager (DataPower, acquired by IBM), Senior Program Manager (Performaworks, acquired by Workscape), and Team Lead (Akamai Technologies). She also has research experience at Microsoft, Silicon Graphics, and Xerox Palo Alto Research Center.
Dr. Xiong earned her B.S. in Computer Science at the University of California at Berkeley, and her Ph.D. in Computer Science at the Media Lab at MIT with her thesis “Visualizing Information Spaces to Enhance Social Interaction." She was a National Science Foundation (NSF) Fellowship Recipient. She holds multiple patents and is very involved in the community, as the Lead Organizer of the Cambridge Parent Summit.
MIT Startup Exchange actively promotes collaboration and partnerships between MIT-connected startups and industry. Qualified startups are those founded and/or led by MIT faculty, staff, or alumni, or are based on MIT-licensed technology. Industry participants are principally members of MIT’s Industrial Liaison Program (ILP).
MIT Startup Exchange is a community of over 1,800 MIT-connected startups with roots across MIT departments, labs and centers; it hosts a robust schedule of startup workshops and showcases, and facilitates networking and introductions between startups and corporate executives.
STEX25 is a startup accelerator within MIT Startup Exchange, featuring 25 “industry ready” startups that have proven to be exceptional with early use cases, clients, demos, or partnerships, and are poised for significant growth. STEX25 startups receive promotion, travel, and advisory support, and are prioritized for meetings with ILP’s 260 member companies.
MIT Startup Exchange and ILP are integrated programs of MIT Corporate Relations.
Cofounder & CEO
Dr. Ryan C.C. Chin is the CEO and Co-founder of Optimus Ride Inc – an MIT spinoff company based in Cambridge, MA that develops self-driving technologies that enable safe, sustainable, and equitable mobility access.
Dr. Chin was the Managing Director of the City Science Initiative at the MIT Media Lab (2012-2015). He conducted Smart Cities research in the areas of urban mobility, housing, energy, and big data analytics. He researched Autonomous Mobility-on-Demand (MoD) Systems – a network of self-driving, shared-use, electric vehicles (EVs). He developed EVs including the GreenWheel, RoboScooter, Persuasive Electric Vehicle, and the CityCar – a foldable, electric, two-person vehicle. Time Magazine named the CityCar the “Automotive Invention of the Year” in 2007. His research led to the MIT Press publication of Reinventing the Automobile: Personal Urban Mobility for the 21st Century by Mitchell, Borroni-Bird, and Burns in 2010.
Dr. Chin advises industry and government agencies on Smart Cities innovations. He is a member of PCAST’s (President’s Council of Advisors on Science and Technology) working group on “Technology and the Future of Cities.” His MIT Professional Education course “Beyond Smart Cities” attracts global participants from corporate, public, and educational sectors. He frequently travels as a speaker at conferences like TEDx, MIT EmTech, and Smart City Expo. His op-ed articles have been featured in publications like the Guardian and BBC. His work has been exhibited at the Cooper Hewitt, Venice Biennale, and London Science Museum.
Dr. Chin has won awards for his research including the Katerva Award (2014) and the 100K Buckminster Fuller Challenge (2009). Esquire Magazine named him as one of the “Best and Brightest Innovators” under the age of 35 (2006). He received at MIT his PhD (2012) and MS (2004) in Media Arts and Sciences and a MArch (2000) in Architecture. He earned both his BCE and BSArch from the Catholic University of America (1997).
The self-driving industry has blurred the distinction between Level 4 and 5 (SAE) autonomy. The reality is that L5 autonomy -- the ability to autonomously in every speed and environmental complexity -- is far from being achieved robustly, reliability, and without safety operators on board the vehicle. An alternative approach is to start in "Geo-fenced" environments such as a corporate/university campus or masterplanned community where the Operating Design Domain (ODD) presents a realistic path to a fully driverless solution (Level 4). This talk discusses the challenges and opportunities in achieving this industry-wide goal.
- Perceptive Automata: AI understanding of human intent for autonomy
- BlinkAI: Imaging AI for autonomy, robotics, sensing
- General Radar: High resolution 4D radar for autonomous machines
- NextDroid: Autonomously measure & predict self-driving capability
- Transit X: Public transit with automated pods on micro-guideways
Cofounder & CTO
Dr. Sam Anthony is the cofounder and CTO of Perceptive Automata, the company that has solved one of the greatest challenges in autonomous vehicle development - understanding humans. Utilizing behavioral science, neuroscience, computer vision, and machine learning he and his team are working towards creating a world in which humans and AVs can safely interact with one another.
An ex-hacker, vision scientist, and expert in human cognition, Sam is fascinated by systems, from artificial neural networks to urban transit grids and the human brain. Prior to founding Perceptive Automata, Sam was the Head of Informatics and Infrastructure at The Many Brains Project, a non-profit organization that provides tests of cognition based on the latest research in psychology and neuroscience. Before that, Sam was the Head of Methods and Test Development at TestMyBrain, a non-profit research initiative that provides measurement tools for people to learn about themselves.
Sam holds a BS in Cognitive Science with a specialization in Computation from the University of California San Diego and a PhD in Cognition, Brain, and Behavior from Harvard University.
Bo Zhu is the CTO of BlinkAI, a spinoff from imaging research he proposed as a postdoctoral research fellow at Harvard and published in Nature. This revolutionary technique rethinks the conventional image reconstruction signal processing pipeline with a fully automated deep learning approach based on human perceptual learning, significantly improving image quality from rapidly acquired low-quality raw data. Zhu received his SB and MEng in electrical engineering from MIT and PhD in biomedical engineering at the Harvard-MIT Division of Health Sciences and Technology (HST). At BlinkAI, he leads the development of machine learning techniques to accelerate high-fidelity CMOS image acquisition and reconstruction in difficult environments using efficient inference that can be deployed on mobile and embedded systems.
Founder & CTO
Dmitry Turbiner invented the world's first SERDES 4D imaging radar and secured seed funding from Kleiner Perkins to found General Radar. His vision to make the world's most powerful sensor to let people experience the benefits of automation remains the company's driving force to this day. Prior to Genrad, Dmitry, previously a microwave engineer at NASA/JPL, served as the Chief Engineer for the COSMIC2/FORMOSAT-7 Radio Occultation Antenna Array. He chose the company's name (Genrad) as an homage to the venerable General Radio of Kendall Square fame. Not surprisingly, Genrad's core team is draws heavily from MIT and is inspired by the US Air Force work done by Margaret Hamilton and her team at MIT Lincoln Labs in the 1960s. Dmitry holds two patents in antenna design and two additional in radar design.
A tech savvy leader who thrives in high growth organizations, Mr. Sam Tolkoff has run divisions in large companies and built teams from scratch at start-ups. He is an expert in robotics and complex product development with a track record of success building new businesses in multiple industries.
Currently he is the CEO of NextDroid, an intelligent machine company with offices in Boston and Pittsburgh.
A Boston native, he resides in Brookline with his wife Becca and their four children. Sam holds two Masters degrees from MIT, where he worked on a robotic tuna fish.
Mike Stanley started Transit X in March 2015 after a series of large snow storms shut down much of Boston's transit system and he looked for solutions to make transportation reliable. After not finding any viable solutions, he decided to start Transit X to create a "Silver Bullet" for transportation.
Mike built his first autonomous robot in 1982 at the age of 12. He is a graduate of MIT with degrees from the Sloan School of Management and in Electrical Engineering and Computer Science.
Additional startups joining:
- SemiKing: Long-range flash LiDAR for autonomous vehicles
- NODAR: Camera-based computer vision systems for automobiles
- Vecna Robotics: Autonomous mobile solutions prioritizing workflows
- Akasha Imaging: Vision AI for optically challenging parts
- Realtime Robotics: Motion planning for autonomous robots & vehicles
- Everactive: Self-powered wireless industrial sensors
- Lightelligence: Photonic AI accelerator chip
Founder & CEO
Kartik Venkataraman is CEO of Akasha Imaging, a computational imaging and deep learning startup in Palo Alto, California that is focused on robotic automation in manufacturing and inspection. His interests lie in commercializing deep technology in the areas of computer vision and imaging with specific focus on business development, product management, and strategic planning. He was previously CTO and Founder of Pelican Imaging that focused on computational array cameras for the mobile imaging market and which was later acquired by Xperi Corporation. Prior to founding Pelican, Kartik headed the Computational Camera group at Micron Imaging (Aptina), and held senior research roles at Intel in 3D and medical imaging where he worked on joint programs with Johns Hopkins Medical School, and the Institute for Systems Science in Singapore. He is a recognized thought leader in the imaging field and holds more than 50 patents in the areas connected to computational imaging. He received his Ph.D. in Computer Science from University of California, Santa Cruz, MS in Computer Engineering from University of Massachusetts, Amherst, and B.Tech (Honors) in Electrical Engineering from the Indian Institute of Technology, Kharagpur.
Peter Howard has a particular passion and interest in business formation and the process of creating order and value out of formative chaos. His roles have included entrepreneur-CEO, investor, and board director. As CEO, Howard has founded and successfully grown five companies, leading two to IPOs, one to strategic sale, and another to major technology license.
Howard led Realtime Robotics in raising $11.7m in funding, landing contracts with global 100 firms and developing the product from initial drawings to commercial. He has also been integral in the creation and launch of hundreds of innovative products as an industry leader in outsourced R&D and manufacturing services businesses based in the US, Japan, France, the Netherlands, Singapore, and China. Howard holds an MS degree from MIT in management and a Professional Director Certification from the American College of Corporate Directors.
Director, Business Development & Partnerships
John Greenfield is the Director of Business Development and Partnerships at Everactive. During his time with the company, he has held various leadership roles, including having responsibility for the sales and people operations functions. Prior to Everactive, Greenfield worked in management consulting in Washington, D.C., where he helped Fortune 100 healthcare and technology clients tackle their most challenging problems related to customer acquisition and retention. he received his MBA from the University of Virginia’s Darden School in 2016, where he was a William Michael Shermet Scholar, the recipient of the Class of 1986 Peter J. Niehaus Scholarship, and the President of the Entrepreneurship and Venture Capital Club. He earned his BA, magna cum laude, from Colgate University, where he studied economics and political science.
VP of Marketing & Business Development
Boaz Efroni Rotman is the VP of Marketing and Business Development at Lightelligence. He is a creative and forward-thinking professional with over 24 years of hands-on global technology in business development, product management, strategic marketing, and sales. Boaz oversaw operations to manage and lead over 20 semiconductor SoCs and products into Consumer, IoT, Cellular, Mobile, Media, Telecom, and Automotive markets through strong technical background and aggressive and innovative go-to-market strategies. Boaz holds a BS in electrical engineering from the Ben-Gurion University in Israel and an MBA from Netanya Academic College in Israel.
Additional startups joining:
- Southie Autonomy: Flexible robotic automation with AR & AI
- blkSAIL: Marine autonomy as a service
Director, Center for Bits and Atoms
MIT Center for Bits and Atoms
Prof. Neil Gershenfeld is the Director of MIT's Center for Bits and Atoms, where his unique laboratory is breaking down boundaries between the digital and physical worlds, from pioneering quantum computing to digital fabrication to the Internet of Things. He's the founder of a global network of over one thousand fab labs, chairs the Fab Foundation, and leads the Fab Academy.
We will discuss research on the essential recursion that is at the heart of autonomy, from assemblers that assemble assemblers, to machines that make machines, to systems that design systems. Then we will explore applications of embodying intelligence in autonomous systems in areas including exponential manufacturing, rapid automation, physical reconfigurability, and personal fabrication.
Alberto Rodriguez is the Class of 1957 Associate Professor at the Mechanical Engineering Department at MIT. Alberto graduated in Mathematics ('05) and Telecommunication Engineering ('06) from the Universitat Politecnica de Catalunya, and earned his PhD (’13) from the Robotics Institute at Carnegie Mellon University. He leads the Manipulation and Mechanisms Lab at MIT (MCube) researching autonomous dexterous manipulation, robot automation, and end-effector design. Alberto has received Best Paper Awards at conferences RSS’11, ICRA’13, RSS’18, IROS'18, and RSS'19, the 2018 Best Manipulation System Paper Award from Amazon, and has been finalist for best paper awards at IROS’16, IROS'18, ICRA'20 and RSS'20. He has led Team MIT-Princeton in the Amazon Robotics Challenge between 2015 and 2017, and has received Faculty Research Awards from Amazon in 2018, 2019 and 2020, and from Google in 2020. He is also the recipient of the 2020 IEEE Early Academic Career Award in Robotics and Automation.
Tactile sensing plays a privileged role in the manipulation chain: it is in direct contact with the world, potentially offering direct observations of shape, motion and force at contact. This potential, however, is in contrast with today robot's limited tactile reasoning, a long-standing challenge in the robotics research community. After decades of advances in sensing instrumentation and processing power, the basic questions remains: How should robots make effective use of sensed contact information? In this talk I will describe efforts in my group to develop planning and control frameworks that exploit tactile feedback, and demonstrate use cases in automated part picking, part handling, and part assembly.
David Mindell is an engineer and historian. An expert in human relationships with robotics and autonomous systems, he has led or participated in more than 25 oceanographic expeditions. From 2005 to 2011 he was Director of MIT’s Program in Science, Technology, and Society. He is the author of five books and co-founder of Humatics Corporation, which develops technologies to transform how robots and autonomous systems work in human environments.
Total transition to full autonomy in manufacturing is unlikely. While “lights out”, fully-automated factories requiring no input have long been a utopian/dystopian vision for the future, even the most automated electronics or production plants still require a large number of workers to set up, maintain, repair, and spearhead the innovation of equipment. Production systems must constantly adapt to rapidly changing conditions. With current technology and even developments in AI, human presence is often superior at providing that flexibility - which will likely remain the case for years to come.
In this talk, David Mindell, MIT Professor and CEO/Founder of Humatics, will discuss how automation has evolved the manufacturing industry, the critical technologies playing a role in this transformation – including the Humatics microlocation platform, which is driving productivity and safety by providing full visibility into intralogistics vehicle operations – and why full autonomy in manufacturing is a distant, unlikely future.