Time: 9:30-10:30 am Eastern Time, Jan 30 (Friday), 2026

Location: MSEE 190

Zoom Link: https://purdue-edu.zoom.us/j/98798335169

Coffee and snacks will be provide.

Autonomous Teams: Where Learning Meets Control

Abstract:

At the frontier of autonomy lies a fundamental question: how can we design teams of agents that reason, act, learn, and memorize cooperatively in dynamic, uncertain environments? In this talk, I will present a unified perspective that integrates learning and control as the foundational principles for building such autonomous teams. In the first half of the talk, I will discuss how my group has advanced the ability of engineered systems to reason and act optimally under uncertainty, and to learn adaptively from interactions with their environment. I will illustrate these ideas through transportation-related applications, including self-learning powertrain control, power management of hybrid electric vehicles, and optimal coordination of connected and automated vehicles. These examples highlight how data-driven control and reinforcement learning can enable autonomous systems to operate safely and efficiently in real time while achieving near-optimal performance. The second half of the talk will focus on the next frontier—building autonomous teams. I will present a theoretical framework grounded in team theory, a mathematical formalism for decentralized stochastic control problems in which multiple agents with asymmetric information cooperate toward a shared objective. I will discuss recent structural results for sequential dynamic team problems with nonclassical information structures, showing how to construct information states that remain invariant to control strategies, thereby enabling dynamic programming decompositions in decentralized settings. These results can aim toward a unifying scientific foundation—what I refer to as the Science of Autonomous Team Intelligence—where teams of agents, whether robotic, vehicular, or human–machine, can reason, act, learn, and memorize collectively, achieving coherent and safe behavior in complex, uncertain environments.

Speaker:

Andreas Malikopoulos is a Professor in the School of Civil & Environmental Engineering and the Director of the Information and Decision Science Lab at Cornell University. Prior to these appointments, he was the Terri Connor Kelly and John Kelly Career Development Professor in the Department of Mechanical Engineering (2017-2023) and the founding Director of the Sociotechnical Systems Center (2019-2023) at the University of Delaware (UD). Before he joined UD, he was the Alvin M. Weinberg Fellow (2010-2017) in the Energy & Transportation Science Division at Oak Ridge National Laboratory (ORNL), the Deputy Director of the Urban Dynamics Institute (2014-2017) at ORNL, and a Senior Researcher in General Motors Global Research & Development (2008-2010). He received a Diploma from the National Technical University of Athens, Greece, and his M.S. and Ph.D. degrees from the University of Michigan, Ann Arbor, in 2004 and 2008, respectively, all in Mechanical Engineering. His research interests are grounded at the intersection of learning and control to enable systems—whether vehicles, robots, or large-scale infrastructures—to operate autonomously and achieve near-optimal performance while safely adapting to and interacting with dynamic environments. His work integrates decision-theoretic foundations with learning-based methods to endow engineered systems with the capability to reason, learn, and act in real time. Dr. Malikopoulos is the recipient of several prizes and awards, including the 2007 Dare to Dream Opportunity Grant from the University of Michigan Ross School of Business, the 2007 University of Michigan Teaching Fellow, the 2010 Alvin M. Weinberg Fellowship, the 2019 IEEE Intelligent Transportation Systems Young Researcher Award, and the 2020 UD’s College of Engineering Outstanding Junior Faculty Award. He has been selected by the National Academy of Engineering to participate in the 2010 German-American Frontiers of Engineering (FOE) Symposium and organize a session on transportation at the 2016 European-American FOE Symposium. He has also been selected as a 2012 Kavli Frontiers of Science Scholar by the National Academy of Sciences. Dr. Malikopoulos is an Associate Editor of Automatica and IEEE Transactions on Automatic Control, and a Senior Editor of IEEE Transactions on Intelligent Transportation Systems. He is a Senior Member of the IEEE, a Fellow of the ASME, and a member of the Board of Governors and Distinguished Lecturer of the IEEE Intelligent Transportation Systems Society.

Organizers: Ziran Wang (ziran@purdue.edu), Yan Gu (yangu@purdue.edu), Yu She (shey@purdue.edu)