Hello there!
I am currently an Assistant Professor in the School of Interactive Computing and a core faculty member of the Institute for Robotics and Intelligent Machines (IRIM) at Georgia Tech.
I direct the Structured Techniques for Algorithmic Robotics (STAR) Lab.
What I do:
I spend most of my time trying to trick people (and sometimes myself!) into thinking robots are smart and collaborative. To aid this illusion, my students and I develop structured computational frameworks and learning algorithms that contain appropriate inductive biases to improve robots’ (data and compute) efficiency, reliability, and self-sufficiency. Our research is motivated by and pertinent to diverse robotics applications, ranging from dexterous manipulation to multi-agent coordination.
P.S.: If you are anything like me, you might like the fact that you can control the playback speed (three dots on the bottom right).
My background
Before starting as an Assistant Professor in 2021, I worked with Sonia Chernova as a Postdoctoral Fellow (and later as a Research Scientist) at Georgia Tech. I received my Ph.D. from the University of Connecticut (UConn) in 2018, where I was a Graduate Fellow of the Institute for Advanced Systems Engineering (IASE) and worked with Ashwin Dani. As part of my PhD dissertation, I developed computational methods for i) learning robot movement primitives from demonstrations with strong theoretical guarantees, and ii) probabilistic inference of the intentions of human partners during close-proximity collaboration. I received my M.S. from the Department of Electrical and Computer Engineering at the University of Florida in 2014, and my B.E. in Instrumentation and Control Engineering from Anna University, Chennai, India in 2012.
Bio
Harish Ravichandar is an Assistant Professor in the School of Interactive Computing and a core faculty member of the Institute for Robotics and Intelligent Machines (IRIM) at Georgia Institute of Technology. He directs the Structured Techniques for Algorithmic Robotics (STAR) Lab. The STAR lab develops structured computational and learning frameworks with appropriate inductive biases to improve robots’ efficiency, reliability, and generalizability. His research is motivated by and pertinent to diverse robotics applications, ranging from dexterous manipulation to multi-agent coordination. His work has been recognized by the NSF CAREER Award, IEEE MRS Best Paper Award, ASME DSCC Best Student Paper Award, P&W Institute for Advanced System Engineering Graduate Fellowship, and Georgia Tech’s College of Computing Outstanding Post-Doctoral Research and Outstanding Research Scientist Awards.
Harish Ravichandar, Ph.D. 