Aude Billard is Professor and head of the LASA Laboratory at the School of Engineering at the Swiss Federal Institute of Technology in Lausanne (EPFL). Prior to this, she was Research Assistant Professor at the Department of Computer Sciences at the University of Southern California, where she retains an adjunct faculty position to this day. Aude Billard received a B.Sc. (1994) and M.Sc. (1995) in Physics from EPFL, with specialization in Particle Physics at the European Center for Nuclear Research (CERN), an M.Sc. in Knowledge based Systems (1996) and a Ph.D. in Artificial Intelligence (1998) from the Department of Artificial Intelligence at the University of Edinburgh. Her research interests focus on machine learning tools to support robot learning through human guidance. This extends also to research on complementary topics, including machine vision and its use in human-robot interaction and computational neuroscience to develop models of learning in humans.

Georgia is a Full Professor for Interactive Robot Perception & Learning at the Computer Science Department of the Technical University of Darmstadt and Hessian.AI. She is the recipient of the renowned Emmy Noether (EN) grant of the German Research Foundation (DFG) for her project iROSA (2021-2027) and has been awarded an ERC Starting Grant in 2024 for her research project SIREN (to start in 2025). Her research span embodied AI, lifelong robot learning, mobile manipulation, and safe human-in-the-loop learning.

Chuchu Fan is an Associate Professor (pre-tenure) in the Department of Aeronautics and Astronautics (AeroAstro) and Laboratory for Information and Decision Systems (LIDS) at MIT. Before that, she was a postdoc researcher at Caltech and got her Ph.D. at the University of Illinois at Urbana-Champaign. She earned her bachelor’s degree from Tsinghua University. Her research group, Realm at MIT, works on using rigorous mathematics, including formal methods, machine learning, and control theory, for the design, analysis, and verification of safe autonomous systems. Chuchu is the recipient of an NSF CAREER Award, an AFOSR Young Investigator Program (YIP) Award, and the 2020 ACM Doctoral Dissertation Award. 

Yunzhu Li an Assistant Professor of Computer Science at Columbia University. Before joining Columbia, He was an Assistant Professor at UIUC CS. He also spent time as a Postdoc at the Stanford Vision and Learning Lab (SVL), working with Fei-Fei Li and Jiajun Wu. He received my PhD from the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT, where he was advised by Antonio Torralba and Russ Tedrake, and he obtained my bachelor's degree from Peking University. His work stands at the intersection of robotics, computer vision, and machine learning, with the goal of helping robots perceive and interact with the physical world as dexterously and effectively as humans do. Yunzhu received the Adobe Research Fellowship and was selected as the First Place Recipient of the Ernst A. Guillemin Master's Thesis Award in Artificial Intelligence and Decision Making at MIT. His research has been published in top journals and conferences, including Nature, NeurIPS, CVPR, and RSS, and featured by major media outlets, including CNN, BBC, The Wall Street Journal, Forbes, The Economist, and MIT Technology Review. He received a B.S. Degree from Peking University and has also spent time at the NVIDIA Robotics Research Lab.

Professor Murphey's research focuses on computational methods in robot active learning, human-machine systems, and emergent phenomena, with applications in neuroscience, health science, robotics, materials science, and machine learning in physical environments. Example applications include assistive exoskeleton control, bio-inspired active sensing, robotic exploration, and software-enabled stroke rehabilitation.

Michael Posa is an Assistant Professor in Mechanical Engineering and Applied Mechanics (MEAM) at the University of Pennsylvania, with secondary appointments in Electrical and Systems Engineering (ESE) and Computer and Information Science (CIS). He leads the Dynamic Autonomy and Intelligent Robotics (DAIR) lab, a group within the Penn GRASP laboratory.  His group focuses on developing algorithms to enable robots to operate both dynamically and safely as they interact with their environments. Michael received his Ph.D. in Electrical Engineering and Computer Science from MIT in 2017 and received his B.S. in Mechanical Engineering from Stanford University in 2007. Before his doctoral studies, he worked as an engineer at Vecna Robotics. He received the NSF CAREER Award in 2023, the RSS Early Career Spotlight in 2023, a Google Faculty Research Award, and a Young Faculty Researcher Award from the Toyota Research Institute. His work has also received awards recognition at TRO, ICRA, RSS, Humanoids, and HSCC.