SK Gupta

SK Gupta

Co-Founder and Chief Scientist, GrayMatter Robotics

Dr. Satyandra K. Gupta is Co-Founder and Chief Scientist at GrayMatter Robotics. He also holds Smith International Professorship at the Viterbi School of Engineering at the University of Southern California and serves as the founding Director of the Center for Advanced Manufacturing. His research interests are Physical AI and human-centered automation. He has published more than five hundred technical articles in journals, conference proceedings, and edited books. He also holds 28 US patents.

He is a fellow of the American Association for the Advancement of Science (AAAS), American Society of Mechanical Engineers (ASME), Institute of Electrical and Electronics Engineers (IEEE), National Academy of Inventors (NAI), Society of Manufacturing Engineers (SME), and Solid Modeling Association (SMA). He currently serves as a member of the Technical Advisory Committee for Advanced Robotics for Manufacturing (ARM) Institute and a member of Association for Advancing Automation (A3) Robotics Technology Strategy Board.

He has received numerous honors and awards for his scholarly contributions, including a Presidential Early Career Award for Scientists and Engineers in 2001 from President Bush, Lifetime Achievement Award from ASME Computers and Information in Engineering Division in 2024, Eli Whitney Productivity Award in 2025, and ASME William T. Ennor Manufacturing Technology Award in 2025.

All Sessions by SK Gupta

October 21, 2026

Why Physical AI Fails in the Real World
10:45 am - 11:30 am
Room 204

A model that performs well in simulation is an important milestone. But it is not proof that a robot is ready for the real world.

The hardest challenges in Physical AI emerge when learned behaviors encounter changing environments, imperfect sensors, limited compute, and unexpected edge cases. This panel will explore what it takes to bridge the gap between training and deployment, including the engineering disciplines required to build reliable robotic systems.

Experts will discuss how teams are addressing challenges across perception, decision-making, and manipulation to create robots that can operate safely and predictably outside the lab.