Antkiewicz, M., M. Kahn, M. Ala, K. Czarnecki, P. Wells, A. Acharya, and S. Beiker, "Modes of Automated Driving System Scenario Testing: Experience Report and Recommendations ", SAE World Congress Experience: SAE, 2020.
MASc student, University of Waterloo (September 2019 - Present)
Research engineer, Autonomoose.net (July 2017 - August 2019)
Pitropov, M., Garcia, D., Rebello, J., Smart, M., Wang, C., Czarnecki, K. and Waslander, S., 2020. Canadian Adverse Driving Conditions Dataset. arXiv preprint arXiv:2001.10117.
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.
A Sarkar, K Czarnecki, "Solution Concepts in Hierarchical Games under Bounded Rationality with Applications to Autonomous Driving", The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21).
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.
InterestsScalable 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