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Vahdat Abdelzad

Postdoctoral Fellow

Vahdat Abdelzad is a Postdoctoral Fellow focusing on the safety aspects of machine learning models. He is studying the safety in terms of out of distribution detection for deep neural networks, explainable artificial intelligence, and active learning.

Matthew Angus

MMath student

BSc Computer Science, Algorithms and Complexity Theory, University of Calgary, Minor in Pure Mathematics

Matt works on semantic segmentation of images for autonomous driving.

Rahul Chandail

MASc student

BASc Electrical and Computer Engineering, University of Windsor, Ontario, Canada

Rahul works on visual odometry and sensor fusion.

Ian Colwell

MASc student

BSc Electrical and Computer Engineering, University of New Brunswick, New Brunswick, Canada

Research interests

  • Autonomous vehicles
  • Software and hardware architectures for cyber-physical systems
  • Robotics

BEng Mechatronics, McMaster University, Ontario, Canada

Research interests

  • autonomous vehicles
  • perception and object classification
  • deep learning neural nets

Samin works on semantic segmentation of images for autonomous driving.

Jaeyoung Lee

Research Associate

Prior affiliations 

  • 2015.09 - 2017.12  Postdoctoral Fellow at the Reinforcement Learning and Artificial Intelligence Lab. at the University of Alberta, AB, Canada.

Selected publications

  • Constrained RL for safety-critical systems
    • Lee, J., Sedwards, S. & Czarnecki, K. (2021).

Matthew Pitropov

Graduated MASc student

MASc student, University of Waterloo (September 2019 - February 2022)

Research engineer, (July 2017 - August 2019)



Pitropov, M., Garcia, D.E., Rebello, J., Smart, M., Wang, C., Czarnecki, K. and Waslander, S., 2021. Canadian adverse driving conditions dataset. The International Journal of Robotics Research40(4-5), pp.681-690.

Rick Salay

Research associate

Rick Salay, PhD, is a systems engineering researcher with broad expertise related to safety, uncertainty, machine-learning and modeling. He has conducted and led internationally recognized research on these topics with major industrial partners and has published over 75 peer-reviewed papers. For the past 5 years he has worked in the Waterloo Intelligent Systems Engineering Lab at University of Waterloo as part of a team developing innovative approaches to the safety of deep neural network based perception in automated driving systems.

Sean Sedwards

Research Assistant Professor


  • Scalable verification and accelerated learning
    • active deep learning for perception in autonomous driving
    • statistical verification of stochastic and nondeterminsitic systems
    • safe reinforcement learning and formal verification of machine-learned systems
    • verification and optimisation of hybrid and timed systems
    • accelerated simulation for rare event verification
    • accelerated learning for prediction of rare events
  • Behaviour modelling, planning and prediction