Claire Bonial

Carlos Nieto-Granda

Michael Dorothy

Michael Dorothy received the B.S. degree in aerospace engineering from Iowa State University, Ames, IA, USA, in 2009 and the Ph.D. degree in aerospace engineering from the University of Illinois at Urbana-Champaign, in 2016.,He has been an Aerospace Engineer for CCDC Army Research Laboratory, Adelphi, MD, USA, since 2015. His research interests include nonlinear dynamics, switched systems, sensitivity-based control, differential game theory, and multiagent collaborative and adversarial planning.

Brian Sadler

Brian M. Sadler received the B.S. and M.S. degrees from the University of Maryland, College Park, and the PhD degree from the University of Virginia, Charlottesville, all in electrical engineering. He is the US Army Senior Scientist (ST) for Intelligent Systems, an IEEE Fellow, and a Fellow of the Army Research Laboratory. He received Best Paper Awards from the IEEE Signal Processing Society in 2006 and 2010, and is an IEEE SP Society Distinguished Lecturer for 2017-2018. He was an Associate Editor of the IEEE Transactions on Signal Processing, IEEE Signal Processing Letters, and EURASIP Signal Processing. He has been a Guest Editor for several journals, including the IEEE JSTSP, the IEEE JSAC, the IEEE SP Magazine, Autonomous Robots, and the International Journal of Robotics Research. His research interests include networked and autonomous intelligent systems, and information science.

Ethan Stump

Ethan Stump is a researcher within the U.S. Army Research Laboratory’s Computational and Information Sciences Directorate, where he works on machine learning applied to robotics and control with a focus on ground robot navigation and human-guided reinforcement learning. He received the Ph.D. and M.S. degrees from the University of Pennsylvania, Philadelphia, and the B.S. degree from the Arizona State University, Tempe, all in mechanical engineering. Dr. Stump is a government lead in intelligence for the ARL Robotics Collaborative Technology Alliance and in distributed intelligence for the ARL Distributed Collaborative Intelligent Systems Technology (DCIST) Collaborative Research Alliance. During his time at ARL, he was worked on diverse robotics-related topics including implementing mapping and navigation technologies to enable baseline autonomous capabilities for teams of ground robots and developing controller synthesis for managing the deployment of multi-robot teams to perform repeating tasks such as persistent surveillance by tying them formal task specifications.

Jonathan Fink

Dr. Jonathan Fink is a researcher working within the Army Research Laboratory’s Computational Sciences Directorate. He received his PhD from the University of Pennsylvania, Philadelphia in 2011. Since joining ARL, he has been integral the research, development, and experimental testing of fundamental capabilities for autonomous ground robots including techniques for mapping and navigation in Army-relevant environments. Dr. Fink focuses on bringing uncertainty-awareness to autonomy algorithms to research and develop systems that are robust to challenging environments with applications ranging from wireless communication maintenance to high-speed control and navigation.