Gaussian Representations for Robot Autonomy: Challenges and Opportunities

University of Delaware, USA

Bio: Gregory S. Chirikjian received undergraduate degrees from Johns Hopkins University in 1988, and a Ph.D. degree from the California Institute of Technology, Pasadena, in 1992. From 1992 until 2021, he served on the faculty of the Department of Mechanical Engineering at Johns Hopkins University, attaining the rank of full professor in 2001. Additionally, from 2004-2007, he served as department chair. Starting in January 2019, he moved to the National University of Singapore, where, he served as Head of the Mechanical Engineering Department, where he hired 14 new professors. Since January 2024 he has served as the mechanical engineering chair at the University of Delaware, where  he has hired three new professors so far.

Chirikjian’s research interests include robotics, applications of group theory in state estimation, information-theoretic inequalities, and applied mathematics more broadly. He is a 1993 National Science Foundation Young Investigator and a 1994 Presidential Faculty Fellow. In 2010 he became a fellow of the IEEE. From 2014-15, he served as a program director for the US National Robotics Initiative, which included responsibilities in the Robust Intelligence cluster in the Information and Intelligent Systems Division of CISE at NSF. Chirikjian is the author of more than 250 journal and conference papers and the primary author of three books, including “Engineering Applications of Noncommutative Harmonic Analysis” (2001) and “Stochastic Models, Information Theory, and Lie Groups, Vols. 1+2” (2009, 2011). In 2016, an expanded edition of his 2001 book was published as a Dover book under a new title, “Harmonic Analysis for Engineers and Applied Scientists.”

University of Technology Sydney, Australia

Bio: Teresa Vidal-Calleja is an Associate Professor and Research Director at the Robotics Institute of the University of Technology Sydney (UTS). Teresa’s main research is in robotics perception combing estimation and machine learning methods. She obtained her PhD degree in automatic control, computer vision, and robotics from the Technical University of Catalonia. She holds a MSc in Mechatronics from CINVESTAV and a BEng in Mechanical Engineering from The National Autonomous University of Mexico. Before joining UTS, she was a postdoctoral fellow at LAAS-CNRS and the Australian Centre for Field Robotics. She is currently Program co-lead at the Australian Cobotics Centre, IEEE Senior member, Associate Editor of IEEE Transactions on Robotics (T-RO) and IEEE Transactions on Field Robotics (T-FR).

Yonsei University, Republic of Korea

Bio: Eunbyung Park is an assistant professor in the Department of Artificial Intelligence at Yonsei University, South Korea. Eunbyung Park obtained his B.S. degree in computer science from Kyung Hee University in 2009, his M.S. degree in computer science from Seoul National University in 2011, and his Ph.D. degree in computer science from the University of North Carolina at Chapel Hill in 2019. Before joining Yonsei University, he was an assistant professor at SKKU, a research scientist at Nuro and an applied scientist at Microsoft. His current research interests include 3D vision and generative modeling.

Idiap Research Insitute, Switzerland

Bio: Dr Sylvain Calinon is a Senior Research Scientist at the Idiap Research Institute and a Lecturer at the Ecole Polytechnique Fédérale de Lausanne (EPFL). He heads the Robot Learning & Interaction group at Idiap, with expertise in human-robot collaboration, robot learning from demonstration, geometric representations and optimal control. The approaches developed in his group can be applied to a wide range of applications requiring manipulation skills, with robots that are either close to us (assistive and industrial robots), parts of us (prosthetics and exoskeletons), or far away from us (shared control and teleoperation). Website: https://calinon.ch

Örebro University, Sweden

Bio: Martin Magnusson is professor in computer science at Örebro University, Sweden, and leads its Robot Navigation & Perception Lab at the Center for Applied Autonomous Sensor Systems. He received a M.Sc. degree in computer science from Uppsala University in 2004 and a Ph.D. degree from Örebro University in 2009. His research interests include 3D mapping and localisation with radar, lidar, and camera data; creation and usage of flow-aware and reliability-aware robot maps; and methods for making use of heterogeneous maps with high uncertainty -- preferrably applied to large autonomous vehicles in challenging environments.

Indiana University, USA

Bio: Lantao Liu is an Associate Professor in the Department of Intelligent Systems Engineering and Department of Computer Science at Indiana University Bloomington. His main research interest lies in Autonomy that integrates real physical robotic systems with data driven methods. He has been working on various autonomous systems involving single or multiple robots,  and his various unmanned vehicles (air, ground, aquatic) have been deployed to the real world with “field trials” in those complex and unstructured environments such as construction sites, emergency sites, farmlands, outdoor air/water, etc. He has received multiple best paper nominations and awards in important robotics venues such as RSS, IROS and DARS. He also received CAREER award and Amazon Machine Learning Research Award.  Before joining Indiana University, he was a Postdoctoral Research Associate in the Department of Computer Science at the University of Southern California during 2015 - 2017. He also worked as a Postdoctoral Fellow in the Robotics Institute at Carnegie Mellon University during 2013 - 2015. He received a Ph.D. from the Department of Computer Science and Engineering at Texas A&M University in 2013.

Carnegie Mellon University, USA

Bio: Kshitij Goel is a Postdoctoral Fellow at the Robotics Institute, Carnegie Mellon University. He earned the Ph.D. and M.S. degrees in Robotics from Carnegie Mellon University in 2024 and 2021, respectively. Earlier, he received the B.Tech. degree in Aerospace Engineering from the Indian Institute of Technology Kharagpur. Kshitij has authored 15 publications in perception and planning for artificially intelligent multi-robot systems, for which he has been a nominee or recipient of three best paper awards (SSRR, TRO). He received the Alan J. Perlis Graduate Student Teaching Award from Carnegie Mellon's School of Computer Science for his contributions to teaching mobile robotics. Kshitij currently conducts research in geometric and statistical methods for multi-modal perception in multi-agent systems.

Massachusetts Insitute of Technology, USA

Bio: Peter Li received the B.A.Sc. in Engineering Science from the University of Toronto, Canada, in 2018. Between 2016 and 2017, he worked in the High-Speed Converters Group at Analog Devices, Toronto, as an integrated circuit engineer. His research focuses on the co-design of memory-efficient algorithms and specialized hardware for localization, mapping, and path-planning on energy constrained devices such as AR/VR headsets, smartphones, and micro-robots.

Massachusetts Institute of Technology, USA

Bio: Soumya Sudhakar is a Ph.D. candidate focusing on autonomous systems in the Aeronautics and Astronautics department at the Massachusetts Institute of Technology. Her research interests center on algorithms for resource-constrained robotics including motion planning, uncertainty estimation for deep neural networks, and decision-making under uncertainty. She received her B.S.E degree in mechanical and aerospace engineering in 2018 from Princeton University and her S.M. degree in aeronautics and astronautics in 2020.