معرفی
Jueming Hu is an Assistant Professor in the Department of Mechanical Engineering at the University of North Dakota (UND), specializing in artificial intelligence applications for autonomous systems. His research integrates theories from AI, formal methods, and optimization to develop novel decision-making techniques for safety-critical systems, particularly focusing on unmanned aerial vehicles and industrial applications.
Dr. Hu received his educational background from:
- Ph.D. in Mechanical Engineering from Arizona State University (2023)
- M.S. in Mechanical Engineering from Arizona State University (2018)
- B.S. in Mechanical Engineering from Southeast University, China (2017)
Dr. Hu's research spans multiple domains within AI and autonomous systems. His primary focus is on reinforcement learning applications for UAV operations, autonomous decision making, and resilient autonomous systems. He has developed novel approaches combining reward machines with reinforcement learning for multi-agent systems, both cooperative and non-cooperative. His work addresses critical challenges in UAV collision avoidance, safety bounds for UAS traffic management, and industrial applications like maintenance scheduling. His research integrates formal methods to ensure safety properties while maintaining system efficiency.
Analysis of Dr. Hu's recent publications reveals a strong focus on applying reinforcement learning to safety-critical autonomous systems. His work demonstrates a progression from theoretical foundations in multi-agent reinforcement learning with reward machines to practical applications in UAV operations and industrial settings. A recurring theme is the integration of formal methods with learning-based approaches to address safety and reliability concerns. His research spans multiple domains including aerospace, industrial engineering, and transportation, showing interdisciplinary impact.
Dr. Hu serves as an external reviewer for several prestigious journals including Transportation Research Part C: Emerging Technologies, IEEE Transactions on Automation Science and Engineering, and Neurocomputing. He has delivered invited talks at Virginia Tech, Missouri University of Science and Technology, Mississippi State University, and Sandia National Laboratories.
Dr. Hu leads the Safe and resiLient Autonomous decision-Making (SLAM) research group at UND, which focuses on advancing research in reinforcement learning driven UAV operations, autonomous decision making, and resilient autonomous systems. The group is currently recruiting research assistants for Spring and Fall 2025.
