Jueming Hu

Assistant Professor

Email: jueming@ou.edu
Office: Felgar Hall 215
Office Hours: Thursdays 3:30-4:30pm
Website: Safe and resiLient Autonomous decision-Making (SLAM) Lab

Education
Ph.D., Mechanical Engineering (2023)
Arizona State University

M.S., Mechanical Engineering (2018)
Arizona State University

B.S., Mechanical Engineering (2017)
Southeast University, China

Research Focus

Dr. Hu’s research focuses on trustworthy autonomous systems, particularly UAVs operating in complex, uncertain, and adversarial environments. Her work integrates artificial intelligence, formal methods, and optimization to advance autonomous decision-making, runtime monitoring, cyberattack detection and mitigation, counter-UAS technologies, and multi-agent coordination.

Experience and Awards

Assistant Professor, School of Aerospace and Mechanical Engineering, University of Oklahoma (Aug 2026–present)
Assistant Professor, Department of Mechanical Engineering, University of North Dakota (Jan 2025 – Aug 2026)
Postdoctoral Researcher, Texas A&M University (Apr 2024 - Jan 2025)
Postdoctoral Researcher, Arizona State University (Jun 2023 - Apr 2024)
Early Career Scholars Program Award, University of North Dakota (2026)

Professional Activities and Organizations

Invited Seminar Speaker, AIAA Intelligent Systems Technical Committee Technical Seminar Series (2026)

Recent Publications

Bhujel, S., Pang, Y., Snyder, P., Tang, C., & Hu, J. (2026). Aerodynamic Effects of Fuselage-Package Separation Distance on UAV Performance. In AIAA AVIATION 2026 Forum (p. 4760).
Momit, M., Hussain, B. Z., Jiang, W., Ammar, M., Pang, Y., Khan, I., Lei, T., & Hu, J. (2026). Deep Q-Network With Lagrangian Relaxation for Autonomous Aircraft Landing. In AIAA SCITECH 2026 Forum (p. 1983).
Hu, J., Ammar, M., Hussain, B. Z., Kim, J., & Khan, I. (2025). Reinforcement-learning-driven integrated detection and mitigation of UAV GPS spoofing attacks. IEEE Internet of Things Journal, 12(18), 36926-36941.
Hu, J., Paliwal, Y., Kim, H., Wang, Y., & Xu, Z. (2024). Reinforcement Learning with Predefined and Inferred Reward Machines in Stochastic Games. Neurocomputing, 599, 128170.
Hu, J., Xu, Z., Wang, W., Qu, G., Pang, Y., & Liu, Y. (2024). Decentralized Graph-Based Multi-Agent Reinforcement Learning Using Reward Machines. Neurocomputing, 564, 126974.
Hu, J., Wang, H., Tang, H., Kanazawa, T., Gupta C., & Farahat A. (2023). Knowledge-Enhanced Reinforcement Learning for Multi-Machine Integrated Production and Maintenance Scheduling. Computers & Industrial Engineering, 185, 109631.
Hu, J., Yang, X., Wang, W., Wei, P., Ying, L., & Liu, Y. (2022). Obstacle Avoidance for UAS in Continuous Action Space Using Deep Reinforcement Learning. IEEE Access, 10, 90623-90634.