Biography and expertise
Dr. Natnael M. Negash is an Assistant Professor of Mechanical Engineering in the Ingram School of Engineering at Texas State University. Prior to joining Texas State University, he was a Postdoctoral Research Associate in the School of Engineering and Computer Science at Baylor University, where he conducted research in the Advanced Vehicle Intelligence and Autonomy (AVIA) Laboratory. He received his Ph.D. in Mechanical Engineering from Texas Tech University and his M.S. in Mechanical Engineering from Addis Ababa University. He previously served as a faculty member in the Department of Mechanical and Industrial Engineering at Addis Ababa Institute of Technology.
His research focuses on integrating dynamics, control, artificial intelligence, optimization, and decision-making for safe and intelligent autonomous mobility systems. His current research interests include safety-critical control, socially aware and game-theoretic decision-making, motion prediction and planning, model predictive control, model predictive path integral control, control barrier functions, reinforcement learning, distributed optimization, large language/vision model–assisted autonomy, automated vehicle platooning, multi-agent robotic systems, and advanced air mobility. His work spans autonomous ground vehicles, unmanned aerial vehicles, eVTOL systems, and networked robotic mobility, with an emphasis on developing safe, reliable, and computationally efficient decision-making and control methods for intelligent engineering systems.
His research focuses on integrating dynamics, control, artificial intelligence, optimization, and decision-making for safe and intelligent autonomous mobility systems. His current research interests include safety-critical control, socially aware and game-theoretic decision-making, motion prediction and planning, model predictive control, model predictive path integral control, control barrier functions, reinforcement learning, distributed optimization, large language/vision model–assisted autonomy, automated vehicle platooning, multi-agent robotic systems, and advanced air mobility. His work spans autonomous ground vehicles, unmanned aerial vehicles, eVTOL systems, and networked robotic mobility, with an emphasis on developing safe, reliable, and computationally efficient decision-making and control methods for intelligent engineering systems.
Education
Doctorate Degree
PhD in Mechanical Engineering
Texas Tech University, 2024
Teaching Interests
Research Interests
Featured scholarly/creative works
- Negash, N. M., Yang, Y., & Yang, J. (n.d.). Socially Compatible Decision-making of Autonomous Vehicles: Probabilistic Rationally Bounded Game Theoretic Approach. Automotive Innovation.
- Negash, N. M., Yang, Y., Tang, S., Yang, J., & Sun, L. (2026). Dual-Layer Safety Projection for Model Predictive Path Integral Control Using Control Barrier Functions in Autonomous Driving. IEEE Open Journal of Control Systems, 5, 666–682. https://doi.org/10.1109/OJCSYS.2026.3740020
Featured awards
- Award / Honor Recipient: Best Paper Award, ASME IDETC/CIE Advanced Vehicle Technologies (AVT). 2022

Featured service activities
- Coordinator / Organizer
American Society of Mechanical Engineers
- Editorial Review Board Member
SAGE Journal of Advanced Robotic Systems
