Nasser Lashgarian Azad

Nasser Lashgarian Azad is an Associate Professor in the Systems Design Engineering department and is also part of the University of Waterloo Centre for Automotive Research (WatCAR), as well as the Waterloo Artificial Intelligence Institute.

He undertook his postdoctoral studies at the Vehicle Dynamics and Control lab in the University of California, Berkeley. His primary research interests lie in control of connected hybrid and electric vehicles, autonomous cars, and unmanned aerial vehicle quadrotors. He is also interested in applications of Artificial Intelligence for solving various engineering problems.

His articles in the above-mentioned areas have been published in high-calibre journal venues, including IEEE Intelligent Transportation Systems Transaction, IEEE Transactions on Vehicular Technology, Engineering Applications of Artificial Intelligence (an IFAC journal), Mechatronics, ASME Journal of Dynamic Systems, Measurement, and Control, Applied Soft Computing, Neurocomputing, and Engineering Optimization.

• Automotive powertrain control
• Vehicle dynamics
• Controls
• Model predictive control
• Automotive
• Autonomous and connected car
• Unmanned vehicle systems
• Intelligent transportation systems
• Electric and hybrid vehicles
• Artificial intelligence
• Optimization
• Optimal and nonlinear control

• SYDE 352L - Control Systems Laboratory
  • Taught in 2014
• SYDE 750 - Topics in Systems Modelling
  • Taught in 2014, 2017, 2018
• SYDE 202 - Seminar
  • Taught in 2014
• SYDE 252 - Linear Systems and Signals
  • Taught in 2014, 2017
• SYDE 352 - Introduction to Control Systems
  • Taught in 2014, 2015, 2017, 2018, 2019
• SYDE 655 - Optimal Control
  • Taught in 2015, 2017, 2018, 2019
• BME 411 - Optimization and Numerical Methods
  • Taught in 2018
• SYDE 411 - Optimization and Numerical Methods
  • Taught in 2018

• B. Sakhdari and N. L. Azad, A distributed reference governor approach to ecological cooperative adaptive cruise control, IEEE Transactions on Intelligent Transportation Systems, 19(5), 2018, 1496 - 1507
• P. Golchoubian and N. L. Azad, Real-time nonlinear model predictive control of a battery-supercapacitor hybrid energy storage system in electric vehicles, IEEE Transactions on Vehicular Technology, 66(11), 2017, 9678 - 9688
• A. Mozaffari, N. L. Azad, J. K. Hedrick, and A. Taghavipour, A hybrid switching predictive controller with proportional integral derivative gains and GMDH neural representation of automotive engines for coldstart control, Engineering Applications of Artificial Intelligence, 48, 2016, 72 - 94
• M. Vajedi and N. L. Azad, Ecological adaptive cruise controller for plug-in hybrid electric vehicles using nonlinear model predictive control, IEEE Intelligent Transportation Systems Transactions, 17(1), 2016, 113 - 122
• A. Mozaffari, M. Vajedi , and N. L. Azad, A robust safety-oriented autonomous cruise control scheme for electric vehicles based on model predictive control and online sequential extreme learning machine with a hyper-level fault tolerance-based supervisor, Neurocomputing, 151, 2015, 845 - 856
• A. Taghavipour, N. L. Azad, and J. McPhee, Real-time predictive control strategy for a plug-in hybrid electric powertrain, Mechatronics, 29, 2015, 13 - 27