Nasser Lashgarian Azad

Nasser Lashgarian Azad is a Professor in the Department of Systems Design Engineering at the University of Waterloo and the Director of the Automation and Intelligent Systems (AIS) Group. Before, he was a Postdoctoral Fellow at the University of California, Berkeley. Dr. Azad’s primary research interests lie in (i) intelligent, safe, and secure controls & automation with applications to automotive systems and autonomous systems like automated vehicles and drones and (ii) innovative applications of AI methods to solve complex modeling, optimization, control, and automation problems.

He has over 90 publications in high-calibre, peer-reviewed journals such as IEEE Transactions on Intelligent Transportation Systems, Artificial Intelligence Review, Applied Soft Computing, IEEE Transactions on Vehicular Technology, Neurocomputing, Engineering Applications of Artificial Intelligence, IEEE Access, Soft Computing, Mechatronics, Vehicle System Dynamics, Engineering Optimization, Journal of Experimental & Theoretical Artificial Intelligence, and ASME Journal of Dynamic Systems, Measurement, and Control. He received an Early Researcher Award in 2015 from the Ontario Ministry of Research and Innovation.

• Artificial Intelligence

• Automation

• Autonomous Vehicles

• Connected Vehicles

• Control Design

• Dynamics

• Electric and Hybrid Vehicles

• Energy Management Systems

• Motion Prediction

• Navigation Systems

• Optimization

• Robotics

• Secure Vehicle Control

• Space Domain Awareness

• Unmanned Aerial Vehicles

• 2009, Postdoctoral Fellow Mechanical Engineering, University of California, Berkeley, USA

• 2007, Doctorate Mechanical Engineering, University of Waterloo, Canada

• 1997, Master of Applied Science Mechanical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Iran

• 1994, Bachelor of Applied Science Mechanical Engineering, Sharif University of Technology, Iran

• BME 411 - Optimization and Numerical Methods
  • Taught in 2023, 2025, 2026
• SYDE 113 - Elementary Engineering Mathematics
  • Taught in 2022
• SYDE 352 - Introduction to Control Systems
  • Taught in 2021, 2023, 2024, 2025, 2026
• SYDE 411 - Optimization and Numerical Methods
  • Taught in 2021, 2022, 2025, 2026
• SYDE 632 - Optimization Methods
  • Taught in 2024
• SYDE 655 - Optimal and Learning-Based Control
  • Taught in 2021, 2023

* Only courses taught in the past 5 years are displayed.

• Wang L., Zheng Z., Wu C., Azad N.L., and Lin Y., Longitudinal and Lateral Control for Discretionary Lane Change via Safe Multi-Agent Reinforcement Learning, IEEE Transactions on Vehicular Technology, 2026.

• Li Q., Gong C., Xu J., Azad N.L., and Lin Y., Co-Optimization of Adaptive Cruise Control and Hybrid Electric Vehicle Energy Management With Clutch Engagement Decision Control, IEEE Transactions on Vehicular Technology, Volume 74, 18340-18352, 2025.

• Zhao X., Li J., Liu M., Zhang J., and Azad N.L., An Optimal Energy Management Strategy With Time-Varying Equivalent Factor Based on Transformer for Multi-Mode Hybrid Electric Mi, IEEE Open Journal of Vehicular Technology, Volume 6, 1749-1759, 2025.

• Sana F., Azad N.L., and Raahemifar K., Pedestrian-Aware Deep RL-Based Decision-Making and Control Framework for Unprotected Left Turns, IEEE Intelligent Vehicles Symposium Proceedings, 2296-2303, 2025.

• Sharma A., Narayan A., Azad N.L., Fischmeister S., and Marksteiner S., AVATAR: Autonomous Vehicle Assessment Through Testing of Adversarial Patches in Real-Time, IEEE Transactions on Intelligent Vehicles, Volume 10, 3208-3221, 2025.

• Masoudi Y., Mahdi Alavi S.M., and Azad N.L., Making the Case for Geometric Identifiability in Electrochemical Impedance Spectroscopy, IEEE Transactions on Control Systems Technology, Volume 34, 524-530, 2026.

• Lohrasbi S., Khoshnevisan L., Narayan A., Azad N.L., and Xiong P., Optimism Induction Attack on Deep Reinforcement Learning with Control Barrier Function Safety Filter for Autonomous Driving, Proceedings of the American Control Conference, 5202-5209, 2025.

• Zhao X., Liu M., Li J., Azad N.L., and Farsi M., Real-Time Energy Management Based on Proximal Policy Optimization With Mask Layer for Hybrid Electric Mining Trucks, IEEE Open Journal of Vehicular Technology, Volume 6, 2988-2999, 2025.

• Golchoubian M., Ghafurian M., Dautenhahn K., and Azad N.L., Uncertainty-Aware DRL for Autonomous Vehicle Crowd Navigation in Shared Space, IEEE Transactions on Intelligent Vehicles, Volume 9, 7931-7944, 2024.

• Kazemi S., Azad N.L., Scott K.A., Oqab H.B., and Dietrich G.B., Satellite Collision Avoidance Maneuver Planning in Low Earth Orbit Using Proximal Policy Optimization, 2024 IEEE Congress on Evolutionary Computation CEC 2024 Proceedings, 2024.

• Farnam A., Farsi M., Ghorbani M., Azad N.L., and Crevecoeur G., Disturbance Propagation in Vehicle Platoons: Symmetric Bidirectional Interconnections, Proceedings of the American Control Conference, 408-413, 2024.

• Xu J., Azad N.L., and Lin Y., Mixed-Integer Optimal Control via Reinforcement Learning: A Case Study on Hybrid Electric Vehicle Energy Management, Optimal Control Applications and Methods, Volume 46, 307-319, 2025.

• Parsonage B., Farsi M., Sanchez L., Azad N.L., and Vasile M., Collision Avoidance Manoeuvre Automation with Deep Reinforcement Learning, Proceedings of the International Astronautical Congress, 132-143, 2024.