Stephen L. Smith, PhD, PEng

Stephen L. Smith is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, a Canada Research Chair in Autonomous Systems, and the Director of the Autonomous Systems Laboratory. He is also Co-Director of the Waterloo Data & Artificial Intelligence Institute (Waterloo.AI). Prior to joining Waterloo, he was a postdoctoral researcher at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). He holds degrees from Queen’s University, the University of Toronto, and UC Santa Barbara.

Prof. Smith is a licensed Professional Engineer and has served in advisory or consulting roles for several leading companies in transportation and robotics. He has served on editorial boards and organizing committees for major IEEE journals and conferences, including the IEEE Transactions on Robotics, the IEEE Transactions on Control of Network Systems, the IEEE Open Journal of Control Systems, the American Control Conference, and International Conference on Robot & Human Interactive Communication (RO-MAN.  His honours include the Early Researcher Award from the Province of Ontario, the NSERC Discovery Accelerator Award, and multiple Outstanding Performance Awards from Waterloo. His research centres on control and optimization for autonomous systems, especially safe motion planning and human-autonomy interaction.

• Autonomous systems

• Robotics

• Artificial intelligence

• Human-robot interaction

• Multi-robot systems

• Machine learning

• Control theory

• Distributed and coordinated control

• Optimization

• Autonomous vehicles

• Intelligent transportation systems

• 2009, PhD, Mechanical Engineering, University of California at Santa Barbara, U.S.A

• 2005, MASc, Electrical and Computer Engineering, University of Toronto, Canada

• 2003, BSc, Applied Science in Engineering Physics, Queen's University, Canada

• 2025 Marsland Faculty Fellow Award

• 2024 Outstanding Performance Award, University of Waterloo

• 2023 Engineering Distinguished Performance Award, University of Waterloo

• 2019 Outstanding Performance Award, University of Waterloo

• 2017 Canada Research Chair in Autonomous Systems

• 2016 Early Researcher Award, Ontario Ministry of Colleges and Universities

• 2016 Outstanding Performance Award, University of Waterloo

• 2023-Present, Co-Director of Waterloo Data & Artificial Intelligence Institute (Waterloo.AI)

• Senior Member, IEEE

• Professional Engineer (PEng), Professional Engineers Ontario

• ECE 380 - Analog Control Systems
  • Taught in 2021
• ECE 406 - Algorithm Design and Analysis
  • Taught in 2020, 2022
• ECE 686 - Filtering and Control of Stochastic Linear Systems
  • Taught in 2020, 2021, 2024, 2025
• MTE 481 - Mechatronics Engineering Design Project
  • Taught in 2023, 2025
• MTE 482 - Mechatronics Engineering Project
  • Taught in 2024

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

• S. Dutta, N. Wilde, and S. L. Smith. Informative Path Planning for Active Regression With Gaussian Processes via Sparse Optimization, IEEE Transactions on Robotics, 41: 2184-2199, 2025.

• Z. F. Dai, Y. Vardhan Pant, and S. L. Smith. Model Predictive Control for Systems With Partially Unknown Dynamics Under Signal Temporal Logic Specifications, IEEE Control Systems Letters, 8: 2931-2936, 2024.

• A. Noormohammadi-Asl, S. L. Smith, and K. Dautenhahn. Human Leading or Following Preferences: Effects on Human Perception of the Robot and the Human-Robot Collaboration, Robotics and Autonomous Systems, 183:104821, 2025.

• A. B. Asghar, S. Sundaram, and S. L. Smith. Multi-Robot Persistent Monitoring: Minimizing Latency and Number of Robots with Recharging Constraints, IEEE Transactions on Robotics, 41:236-252, 2024.

• N. Wilde, S. L. Smith, and J. Alonso-Mora. Scalarizing Multi-Objective Robot Planning Problems using Weighted Maximization, In IEEE Robotics and Automation Letters, 9(3):2503-2510, 2024

• A. Botros, N. Wilde, A. Sadeghi, J. Alonso-Mora and S. L. Smith. Regret-based Sampling of Pareto Fronts for Multi-Objective Robot Planning Problems, IEEE Transactions on Robotics, 40: 3778-3794, 2024.

• B. Gilhuly, A. Sadeghi, and S. L. Smith. Estimating Visibility from Alternate Perspectives for Motion Planning with Occlusions, IEEE Robotics and Automation Letters, 9(6): 5583-5590, 2024.

• A. Noormohammadi-Asl, S. L. Smith, and K. Dautenhahn. To Lead or to Follow? Adaptive Robot Task Planning in Human-Robot Collaboration, January 2024. Under Revision.

• M. Ramesh, F. Imeson, B. Fidan, and S. L. Smith. Anytime Replanning of Robot Coverage Paths for Partially Unknown Environments, IEEE Transactions on Robotics, 40: 4190-4206, 2024.

• M. Ramesh, F. C. Imeson, S. L. Smith, and B. Fidan. System and method of replanning for coverage of environments with unknown obstacles. US Patent App. 18/593,009. Mar. 2024.

• M. Ramesh, F. C. Imeson, S. L. Smith, and B. Fidan. System and method of minimum turn coverage of arbitrary non-convex regions. US Patent 17/943,634. 2023.

• A. Sadeghi, B. Gilhuly, S. L. Smith, P. Yadmellat, and K. Rezaee. Systems, Methods, and Media for Occlusion-Aware Motion Planning. US Patent 11,834,077. 2023.

• Z. Huang, H. Singh, S. Tajeddin, and S. L. Smith. Method, system and apparatus for generating navigational data. US Patent 10,823,572. 2020.

• K. C. Jen, H. Singh, and S. L. Smith. Fixed segmented lattice planning for a mobile automation apparatus. US Patent 10,591,918. 2020.

• Three professors named to Canada Research Chairs