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.
Profiles
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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).
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.
Interests
- 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