Robot Learning Workshop

October 14-15, 2019


Robot Learning Workshop October 14-15, 2019


This 2 day NSF-funded workshop aims at bringing together leading researchers in the emerging field of robot learning to foster interdisciplinary communication and collaboration. This workshop will offer presentations by invited speakers who are distinguished researchers and experts in related areas to robotics, controls and machine learning.

Deadline to register: Tuesday, October 1, 2019

Overview of Workshop 

The workshop will offer a series of presentations on emerging directions within intersection of robotics, deep and reinforcement learning, control systems, and operational research. The primary objective of this event is to facilitate interactions between researchers from different disciplines interested in designing and implementing the envisioned autonomous robots. The broader impact of this workshop will be to inspire the research community on new interdisciplinary directions in robotics, controls, and machine learning. We believe that presenting challenging and important problems, in a coherent fashion, to these communities will open up tremendous intellectual opportunities for research and attract young researchers and students to this timely and important research field.

Organizing Committee:

  • Nader Motee, Lehigh University
  • Hector Munoz-Avila, Lehigh University
  • Katya Scheinberg, Cornell University
  • Jeff Trinkle, Lehigh University

 Confirmed Speakers

  • Amir Ali Ahmadi, Princeton University
  • Yiannis Aloimonos, University of Maryland
  • Radu Balan, University of Maryland
  • Kostas Daniilidis, University of Pennsylvania
  • Jim Donlon, National Science Foundation (NSF)
  • Maria Gini, University of Minnesota
  • David Held, Carnegie Mellon University
  • Na Li, Harvard University
  • Nikolai Matni, University of Pennsylvania
  • Marco Pavone, Stanford University
  • Don Perlis, University of Maryland
  • Gita Sukthankar, University of Central Florida
  • Ufuk Topcu, University of Texas
  • Alexander Toshev, Google AI
  • Kyriakos Vamvoudakis, Georgia Tech
  • Rene Vidal, Johns Hopkins University

Workshop supported by: