CASE2025 Workshop

ABSTRACT:

While robotics and AI are rapidly changing the landscape of jobs and work, there are numerous obstacles to overcome to establish new industries and job roles, all while striving to improve productivity and the overall quality of work life. This workshop is designed to bring together individuals involved in robotics across various sectors. Its goal is to facilitate discussions on cutting-edge robotics research, including topics like human-robot collaboration, motion planning and control, and artificial intelligence. By examining these advancements, we seek to understand how robotics and AI will impact future work across industries such as manufacturing, construction, transportation, warehousing, and more. Through collaborative exploration and discussion, the workshop aims to shed light on the potential implications of these technologies for the workforce of tomorrow.

TENTATIVE PROGRAM:

SPEAKERS:

Jingang Yi, Professor

Rutgers University

Title: Wearable Sensing and Assistive Exoskeletons for Enhancing Worker Mobility and Safety in Construction

Bio: Professor Jingang Yi received the B.S. degree in electrical engineering from Zhejiang University in 1993, the M.Eng. degree in precision instruments from Tsinghua University in 1996, and the M.A. degree in mathematics and the Ph.D. degree in mechanical engineering from the University of California, Berkeley, in 2001 and 2002, respectively. He is currently a Full Professor in mechanical engineering and Peter D. Cherasia Faculty Scholar at Rutgers University. His research interests include physical human-robot interactions, autonomous robotic and vehicle systems, mechatronics, dynamic systems and control, automation science and engineering. Prof. Yi is a Fellow of ASME and a Senior Member of IEEE. He has received several awards, including the 2018 Japan Society for the Promotion of Science (JSPS) Invitational Fellowship for Research, 2017 Rutgers Chancellor’s Scholars, 2014 ASCE Charles Pankow Award for Innovation, the 2013 Rutgers Board of Trustees Research Fellowship for Scholarly Excellence, and the 2010 NSF CAREER Award. He has coauthored several best papers in IEEE Transactions on Automation Science and Engineering and at IEEE/ASME AIM, ASME DSCC, and IEEE ICRA, etc. He currently serves as a Senior Editor for IEEE Transactions on Automation Science and Engineering and Editor-in-Chief of Conference Editorial Board for IEEE International Conference on Automation Science and Engineering (CASE). He also served as Associate Editor of IFAC journals Control Engineering Practice, Mechatronics, IEEE/ASME Transactions on Mechatronics, IEEE Transactions on Automation Science and Engineering, IEEE Robotics and Automation Letters, and ASME Journal of Dynamic Systems, Measurement and Control and a Senior Editor of IEEE Robotics and Automation Letters.

Yu She, Assistant Professor

Purdue University

Title: Multi-Modal Sensing and Neural-Symbolic Manipulation

Bio: Dr. Yu She is an assistant professor at Purdue University Edwardson School of Industrial Engineering. Prior to that, he was a postdoctoral researcher in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT from 2018 to 2021. He earned his PhD degree in the Department of Mechanical Engineering at the Ohio State University in 2018. His research is at the intersection of mechanism design, tactile sensing, intelligent control, and robot learning. He is a recipient of the ASME Feudenstein Young Investigator Award (2025), Showalter Early Investigator Award (2024) and the Google Research Scholar Award (2022) and multiple paper recognitions, including the Best Paper Award Finalist for the 2020 ASME Journal of Mechanisms and Robotics, the Best Paper Award Finalist at the 2020 Robotics: Science and Systems (RSS) Conference, the Best Paper Award at the 2018, ASME Dynamic Systems & Control Conference (DSCC), and the Best Paper Award Finalist at the 2013 IEEE International Conference on Robotics and Biomimetics (ROBIO).

Michael Yip, Associate professor

UC San Diego

Title: Robotics, AI, & Healthcare: Why we need Autonomous Robots and what the Future May Look Like

Bio: Michael Yip is an Associate Professor of Electrical and Computer Engineering at UC San Diego, and Director of the Advanced Robotics and Controls Laboratory (ARCLab). His group currently focuses on surgical robots, biomimetic design, and robot learning. His research has received several best paper awards and nominations at ICRA and IROS and RA-L, and he has been recognized by the NSF CAREER award, NIH Trailblazer award, and as a RAS Distinguished Lecturer. Several of his research has led to founded startups, and he was named the Faculty Innovator of the Year at UCSD in 2024, and elected into the National Academy of Inventors. Dr. Yip was previously a Disney Research in 2014 and Amazon Robotics in 2018. He received a B.Sc. in Mechatronics Engineering from the University of Waterloo, an M.S. in Electrical Engineering from the University of British Columbia, and a Ph.D. in Bioengineering from Stanford University.

Tan Chen, Assistant Professor

Michigan Tech

Title: Fractional-Order Dynamics Meets Neural Networks in Large Scale Robotic Systems.

Bio: Dr. Tan Chen is an Assistant Professor in the Department of Electrical and Computer Engineering at Michigan Tech. Prior to joining Tech, Dr. Chen was a Postdoctoral Research Associate affiliated with the Coordinated Science Laboratory at the University of Illinois Urbana-Champaign. He received his PhD degree in Aerospace and Mechanical Engineering from the University of Notre Dame. Prior to that, he received his BS degree in Mechanical Engineering from Shanghai Jiao Tong University (SJTU), China, and a joint MS degree from SJTU and École des Mines de Douai, France. He was an Eiffel Scholarship recipient in France and received the outstanding graduate student teaching award at the University of Notre Dame. He was selected as a DAAD AInet fellow for the Postdoc-NeT-AI in AI and robotics. His research interests include robotics, control theory, dynamical systems, and Artificial Intelligence (AI) with health care and smart manufacturing applications.

Chen Tang, Incoming Assistant Professor

University of California, Los Angeles

Title: Learning and Control for Human-Centered Autonomy.

Bio: Chen Tang is an incoming assistant professor at the Department of Civil and Environmental Engineering at the University of California, Los Angeles. He was a postdoctoral fellow in Computer Science at the University of Texas at Austin (UT Austin) and a postdoctoral scholar in Mechanical Engineering at the University of California, Berkeley (UC Berkeley). He received his Ph.D. degree in Mechanical Engineering from UC Berkeley in 2022, advised by Prof. Masayoshi Tomizuka, and his B.Eng. degree in Mechanical Engineering from the Hong Kong University of Science and Technology (HKUST) in 2016. He is a recipient of the IEEE ITSC Runner-up Best Student Paper Award (2018), the ASME DSCD Rising Star Award (2022), and was named an RSS Pioneer in 2023. His research interest lies at the intersection of control, robotics, and learning, with applications in autonomous driving and robot navigation.

Neel Dhanaraj, Incoming Lead Robotics Engineer

GrayMatter Robotics

Title: Bringing Collaborative Robot Teams to High-Mix Manufacturing: Optimal yet Adaptable Decision-Making in Semi-Structured Environments.

Bio: Neel Dhanaraj is an incoming Lead Robotics Engineer at GrayMatter Robotics, where he will develop intelligent robotic systems for high-mix manufacturing environments. His research interests focus on integrating classical, advanced robotics and planning methods with new deep learning–based approaches to create interpretable neuro-symbolic AI systems that operate robustly in semi-structured settings, balancing optimal decision-making with adaptability to environmental variation. Neel earned his Ph.D. in Mechanical Engineering from the University of Southern California’s Center for Advanced Manufacturing, where he developed iterative decision-making algorithms that generate high-quality plans accounting for variability in task uncertainty, execution failures, human preferences, and geometric configurations, as well as robotic systems evaluated on tasks such as assembly, spray coating, and surface heating. He previously received his B.S. and M.S. in Mechanical Engineering from Worcester Polytechnic Institute.

Minghui Zheng, Associate Professor

Texas A&M University

Title: Robotics and Human-Robot Collaboration for Disassembly and Remanufacturing.

Bio: Minghui Zheng received the B.S. degree in engineering mechanics in 2008 and M.S. degree in control science and engineering in 2011, both from Beihang University, China, and the Ph.D. degree in mechanical engineering from University of California, Berkeley, CA, USA, in 2017. She is currently an Associate Professor of the J. Mike Walker '66 Department of Mechanical Engineering, Texas A&M University, TX, USA. Before that, she was an Associate Professor at the University at Buffalo, NY, USA. Her research interest lies in learning, planning, and control with applications to several areas that are of vital importance to remanufacturing and robotics. Dr. Zheng was the recipient of the NSF CAREER Award in 2021.

ORGANIZERS:

Minghui Zheng
Associate Professor
Texas A&M University

Hao Su
Associate Professor
New York University

Tan Chen
Assistant Professor
Michigan Tech

Jingang Yi
Professor
Rutgers University