Faculty Spotlight: CoRL accepts esteemed work of Asst. Prof Jayaraman

The international Conference on Robot Learning (CoRL) has accepted the renowned work of CIS and GRASP Lab Assistant Professor Dinesh Jayaraman.

According to their site, the “CoRL is a selective, single-track conference for robot learning research, covering a broad range of topics spanning robotics, ML and control, and including theory and applications.” With an acceptance rate of 34% this year, the conference was able to increase their intake slightly due to the fact that it’s taking place solely online. The call for 2020 submissions featured a variety of topics such as Imitation learning and (inverse) reinforcement learning, Bio-inspired learning and control and Multimodal perception, sensor fusion, and computer vision.

Jayaraman’s paper, titled Model-Based Inverse Reinforcement Learning from Visual Demonstrations, was co-authored by Neha Das, Sarah Bechtle, Todor Davchev, Dinesh Jayaraman, Akshara Rai and Franziska Meie. All accepted papers are also published in the Journal of Machine Learning Research (JMLR) Workshop & Conference Proceedings series.

The fourth annual CoRL 2020, whose previous hosting sites include Osaka, Japan, Zurich, Switzerland and Mountain View, USA, will be held virtually from November 16 – 18.