Bosen Lian

Bosen Lian is an Assistant Professor in the Department of Electrical and Computer Engineering at Auburn University's College of Engineering. He received his Ph.D. in Electrical Engineering from the University of Texas at Arlington, where he also served as a postdoctoral researcher and adjunct professor before joining Auburn in August 2023. His research focuses on distributed control, reinforcement learning, game theory, and their integration in cyber-physical and robotic systems.

Research Interests: His work centers on designing safe, optimal, and resilient multi-agent systems through data-driven control and inverse reinforcement learning. Key areas include cooperative control, graphical games, robotics, distributed estimation, and anomaly detection in autonomous systems. He applies these methods to robotic platforms such as robot arms, unmanned vehicles, and sensor networks.

His recent publications show a strong trend in leveraging inverse reinforcement learning for multi-agent and adversarial systems, with applications in tracking, estimation, and optimal control. He frequently publishes in top IEEE journals and Automatica, demonstrating consistent contributions to control theory and machine learning integration.

Scientific Awards and Recognition:

• Appointed Associate Editor at IEEE Transactions on Neural Networks and Learning Systems
• Appointed Associate Editor at IEEE Transactions on Cybernetics
• Appointed Associate Editor at Transactions of the Institute of Measurement and Control
• Published first textbook: 'Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games'

Advising and Grants: He actively mentors students and researchers such as Wenqian Xue, Vrushabh S. Donge, and others, many of whom are co-authors on his publications. While specific grant details are not listed, his continuous publication output and editorial appointments suggest strong research support and funding. His lab conducts rigorous theoretical analysis alongside practical robotic applications.

Labs and Teams: His research group focuses on cyber-physical feedback systems, working on both theoretical algorithms and real-world implementations. The team explores dynamic clustering, consensus, and learning-based control in networked environments, maintaining a balance between provable guarantees and data efficiency.