Biography
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.
Research Interests
Social-aware/interactive decision-making of AVs
Safety-critical control for autonomous vehicles
DRL for decision-making and control
Connected and automated platoon control
Drone swarm scheduling
Advanced air mobility (AAM)
Safety-critical control for autonomous vehicles
DRL for decision-making and control
Connected and automated platoon control
Drone swarm scheduling
Advanced air mobility (AAM)
Teaching Interests
Nonlinear Dynamics and Control
Linear Control Theory
Mechanics of Materials/Strength of Materials
Engineering Mechanics (Dynamics)
Optimal Control
Introduction to System Dynamics
Introduction to Reinforcement Learning
Linear Control Theory
Mechanics of Materials/Strength of Materials
Engineering Mechanics (Dynamics)
Optimal Control
Introduction to System Dynamics
Introduction to Reinforcement Learning