Confirmed speakers

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Dr. Pierre E. Dupont

Dr. Pierre E. Dupont

Pierre E. Dupont is Chief of Pediatric Cardiac Bioengineering and holder of the Edward P. Marram Chair at Boston Children’s Hospital. He is also a Professor of Surgery at Harvard Medical School. His research group develops robotic instrumentation and imaging technology for medical applications. He received the BS, MS and PhD degrees in Mechanical Engineering from Rensselaer Polytechnic Institute, Troy, NY, USA. After graduation, he was a Postdoctoral Fellow in the School of Engineering and Applied Sciences at Harvard University, Cambridge, MA, USA. He subsequently moved to Boston University, Boston, MA, USA where he was a Professor of Mechanical Engineering and Biomedical Engineering. He is an IEEE Fellow, a former Senior Editor for IEEE Transactions on Robotics and is a member of the Advisory Board for Science Robotics.

Dr. Robert J. Webster III

Dr. Robert J. Webster III

Robert J. Webster III is the Richard A. Schroeder Professor of Mechanical Engineering at Vanderbilt University. He received his B.S. in electrical engineering from Clemson University in 2002, and his M.S. and Ph.D. in mechanical engineering from the Johns Hopkins University in 2004 and 2007. In 2008, he joined the mechanical engineering faculty of Vanderbilt University, where he currently directs the Medical Engineering and Discovery Laboratory. He founded and serves on the steering committee for the Vanderbilt Institute for Surgery and Engineering, which brings together physicians and engineers to solve challenging clinical problems. He is the founder and President of Virtuoso Surgical, Inc. and EndoTheia, Inc. which are commercializing technologies invented in his laboratory, and have raised approximately $25M in private capital and grant funding to date. Prof. Webster’s research interests include surgical robotics, medical device design, image-guided surgery, and continuum robotics.

Dr. Ibrahim Volkan Isler

Dr. Ibrahim Volkan Isler

Volkan Isler is a Professor in the Computer Science and Engineering Department at the University of Minnesota where he is also a resident fellow at the Institute on Environment and 2010-2012 McKnight Land-Grant Professor. He is currently a visiting professor at Samsung AI Research Center in NY. In 2008, he received the National Science Foundation’s Young Investigator Award (CAREER). From 2009 to 2015, he chaired IEEE Society of Robotics and Automation (RAS) ‘s Technical Committee on Networked Robots. He also served as an Associate Editor for IEEE Transactions on Robotics and IEEE Transactions on Automation Science and Engineering. He is currently an Editor for RAS Conference Editorial Board. His research interests are primarily in robotics, computer vision, sensor networks and geometric algorithms, and their applications in agriculture and environmental monitoring.

Dr Peter Stone

Dr. Peter Stone

Peter is the Executive Director of Sony AI America. He is also the founder and director of the Learning Agents Research Group (LARG) within the Artificial Intelligence Laboratory in the Department of Computer Science at The University of Texas at Austin, as well as associate department chair and Director of Texas Robotics. In 2013 he was awarded the University of Texas System Regents’ Outstanding Teaching Award and in 2014 he was inducted into the UT Austin Academy of Distinguished Teachers, earning him the title of University Distinguished Teaching Professor. Professor Stone’s research interests in Artificial Intelligence include machine learning (especially reinforcement learning), multiagent systems, and robotics. Professor Stone received his Ph.D. in Computer Science in 1998 from Carnegie Mellon University. From 1999 to 2002 he was a Senior Technical Staff Member in the Artificial Intelligence Principles Research Department at AT&T Labs – Research. He is an Alfred P. Sloan Research Fellow, Guggenheim Fellow, AAAI Fellow, IEEE Fellow, AAAS Fellow, ACM Fellow, Fulbright Scholar, and 2004 ONR Young Investigator. In 2007 he received the prestigious IJCAI Computers and Thought Award, given biannually to the top AI researcher under the age of 35, and in 2016 he was awarded the ACM/SIGAI Autonomous Agents Research Award.

Dr. Stefanos Nikolaidis

Dr. Stefanos Nikolaidis

Dr. Stefanos Nikolaidis is an Associate Professor of Computer Science at the University of Southern California and leads the Interactive and Collaborative Autonomous Robotics Systems (ICAROS) lab. His research draws upon expertise on artificial intelligence, procedural content generation and quality diversity optimization and leads to end-to-end solutions that enable deployed robotic systems to act robustly when interacting with people in practical, real-world applications. Stefanos completed his PhD at Carnegie Mellon’s Robotics Institute and received an MS from MIT, a MEng from the University of Tokyo and a BS from the National Technical University of Athens. Stefanos has also worked as a research associate at the University of Washington, as a research specialist at MIT and as a researcher at Square Enix in Tokyo. He was recognized with an NSF CAREER award in 2022 for his work on “Enhancing the Robustness of Human-Robot Interactions via Automatic Scenario Generation.” Stefanos’ research has also been recognized with best paper awards and nominations from the IEEE/ACM International Conference on Human-Robot Interaction, The Genetic and Evolutionary Computation Conference, the International Conference on Intelligent Robots and Systems, and the International Symposium on Robotics.

Dr. Jessie Y. C. Chen

Dr. Jessie Y. C. Chen

Jessie Y. C. Chen received the B.A. degree in linguistics from National Tsing-Hua University, Hsinchu, Taiwan, in 1987, the M.A. degree in communication studies from the University of Michigan, Ann Arbor, MI, USA, in 1989, and the Ph.D. degree in applied experimental and human factors psychology from the University of Central Florida, Orlando, FL, USA, in 2000.,She is a Senior Research Psychologist (ST) for Soldier Performance in Socio-Technical Systems with U.S. Army Research Laboratory. Her research interests include human–agent teaming, agent transparency, human-robot interaction, and human supervisory control.,Dr. Chen is an Associate Editor for the IEEE Transactions on Human-Machine Systems and IEEE Robotics and Automation—Letters, and she Guest Edited a special issue on “Human-Autonomy Teaming” for Theoretical Issues in Ergonomics Science, published in 2018.

Dr. Michael T. Tolley

Dr. Michael T. Tolley

Michael T. Tolley is Associate Professor in Mechanical and Aerospace Engineering, and director of the Bioinspired Robotics and Design Lab at the Jacobs School of Engineering, UC San Diego (bioinspired.eng.ucsd.edu). Before joining the mechanical engineering faculty at UCSD in the fall of 2014, he was a postdoctoral fellow at the Wyss Institute for Biologically Inspired Engineering, Harvard University. He received the Ph.D. and M.S. degrees in mechanical engineering with a minor in computer science from Cornell University in 2009 and 2011, respectively. His research seeks inspiration from nature to design robotic systems with the versatility, resilience, and efficiency of biological organisms. Example topics include soft robots, origami robots, and systems capable of self-assembly. His work has appeared in leading academic journals including Science and Nature, and has been recognized by awards including a US Office of Naval Research Young Investigator Program award and a 3M Non-Tenured Faculty Award. He is active in the robotics community, serving in multiple associate editor and conference organizer roles including as Program Chair of the IEEE International Conference on Soft Robotics (RoboSoft) in 2020 and General Chair in 2024. Prof. Tolley is a Senior Fellow of the Institute of Electrical and Electronics Engineers (IEEE), a member of the IEEE Robotics and Automation Society (RAS), and of the American Society of Mechanical Engineers (ASME).

Dr. Monica A Daley

Dr. Monica A Daley

Monica earned her undergraduate degree in Biology at University of Utah. She was inspired to become a physiologist through her research on human running and breathing with Dennis Bramble and David Carrier. She then spent a year working as a research technician with Franz Goller, investigating motor control of singing in zebra finches. These experiences initiated a long-standing fascination with the complex interplay of mechanics and neural control. Monica earned her Ph.D. from Harvard University in Organismic and Evolutionary Biology, investigating muscle-tendon dynamics and biomechanics of bipedal locomotion. Her PhD research was supported by a Predoctoral Fellowship from the Howard Hughes Medical Institute and supervised by Andrew Biewener. After her PhD, Monica trained in neuromechanics as an NSF Postdoctoral Fellow with Dan Ferris at the University of Michigan. Daley was faculty in the Structure and Motion Lab at the Royal Veterinary College (RVC) from 2008-2019 and joined the UCI Department of Ecology and Evolutionary Biology in Summer 2019.

Dr. Nanshu Lu

Dr. Nanshu Lu

Dr. Nanshu Lu is the Frank and Kay Reese Professor at the University of Texas at Austin. She received her B.Eng. with honors from Tsinghua University, Beijing, her Ph.D. from Harvard University, and then Beckman Postdoctoral Fellowship at UIUC. Her research concerns the mechanics, materials, manufacture, and human / robot integration of soft electronics. She is a Clarivate (Web of Science) highly cited researcher and a Fellow of the American Society of Mechanical Engineers (ASME). She is on the Board of Directors of the Society of Engineering Science (SES). She is currently an Associate Editor of Nano Letters and Journal of Applied Mechanics. She has been named 35 innovators under 35 by MIT Technology Review (TR 35) and iCANX/ACS Nano Inaugural Rising Star. She has received US NSF CAREER Award, US ONR and AFOSR Young Investigator Awards, 3M non-tenured faculty award, and the ASME Thomas J.R. Hughes Young Investigator Award. She was selected as one of the five great innovators on campus and five world-changing women at the University of Texas at Austin.

Dr. Yisong Yue

Dr. Yisong Yue

Yisong Yue is a Professor of Computing and Mathematical Sciences at the California Institute of Technology, and a Principal Scientist at Latitude AI. He was previously a research scientist at Disney Research. Before that, he was a postdoctoral researcher in the Machine Learning Department and the iLab at Carnegie Mellon University. He received a Ph.D. from Cornell University and a B.S. from the University of Illinois at Urbana-Champaign. Yisong is also the Senior Program Chair of the ICLR 2024 (International Conference on Learning Representations). Yisong’s research interests are centered around machine learning, and in particular getting theory to work in practice. To that end, his research agenda spans both fundamental and applied pursuits, from novel learning-theoretic frameworks all the way to deployment in autonomous driving on public roads. His work has been recognized with multiple paper awards and nominations, including in robotics, computer vision, sports analytics, machine learning for health, and information retrieval. At Latitude AI, he works on machine learning approaches to behavior modeling and motion planning for autonomous driving.

Dr. Evangelos Theodorou

Dr. Evangelos Theodorou

Evangelos Theodorou earned his diploma in electronic and computer engineering from the Technical University of Crete (TUC), Greece in 2001. He has also received a MSc in production engineering from TUC in 2003, a MSc in computer science and engineering from University of Minnesota in spring of 2007 and a MSc in electrical engineering on dynamics and controls from the University of Southern California(USC) in Spring 2010. In May of 2011 he graduated with his PhD, in computer science at USC. After his PhD, he became a postdoctoral research associate with the department of Computer Science and Engineering, University of Washington, Seattle. In July 2014 he joined the faculty of the Daniel Guggenheim School of Aerospace Engineering at Georgia Institute of Technology as assistant professor. His theoretical research spans the areas of control theory, machine learning, information theory and statistical physics. Applications involve autonomous planning and control in robotics and aerospace systems, bio-inspired control and design.