NCCR Automation seminar series - Prof. Dorsa Sadigh
Our NCCR Automation Seminar Series continues with Prof. Dorsa Sadigh from Stanford University. Dorsa will give this talk together with Erdem Biyik, one of her PhD candidates.
Title: Interactive Robotics through the Lens of Learning
Abstract: There have been significant advances in the field of robot learning in the past decade. However, many challenges still remain when considering how robot learning can advance interactive agents such as robots that collaborate with humans, and how interactions can enable more effective robot learning. This introduces an opportunity for developing new robot learning algorithms that can help advance interactive autonomy. In this talk, we will discuss a formalism for human-robot interaction built upon ideas from representation learning. This formalism provides an orthogonal perspective to theory of mind, and provides a path for scalable partner modeling. Specifically, we will first discuss the notion of latent strategies - low dimensional representations sufficient for capturing non-stationary interactions. We will then talk about some of the challenges of learning such representations when interacting with humans, and how we can develop data-efficient techniques that enable actively learning computational models of human behavior from interaction data: demonstrations, preferences, or physical corrections.
Biography: Dorsa Sadigh is an Assistant Professor in the Computer Science and Electrical Engineering at Stanford University. Her research interests lie at the intersection of robotics, learning, and control theory. Specifically, she is interested in developing efficient algorithms for safe and adaptive human-robot and multi-agent interactions. Dorsa received her doctoral degree in Electrical Engineering and Computer Sciences (EECS) at UC Berkeley in 2017, and received her bachelor’s degree in EECS at UC Berkeley in 2012. She is recognized by awards such as the NSF CAREER award, the AFOSR Young Investigator award, the IEEE TCCPS early career award, MIT TR35, as well as industry awards such as the JP Morgan, Google, and Amazon faculty research awards.
Erdem Biyik's biography: Erdem Biyik is a Ph.D candidate in the Electrical Engineering department at Stanford. He has received his B. Sc degree from Bilkent University, Turkey, in 2017; and M. Sc. degree from Stanford University in 2019. He is interested in enabling robots to actively learn from various forms of human feedback and designing adaptive robot policies to improve the efficiency of multi-agent systems both in cooperative and competitive settings. He also worked at Google as a research intern in 2021 where he adapted his active robot learning algorithms to recommender systems.
You can find Prof. Sadigh and Erdem Biyik's talk on our YouTube channel.
