Parvin Malekzadeh Hi! I'm a Postdoctoral Fellow in the Operations Management and Statistics department at the Rotman School of Management, University of Toronto (UofT). My research focuses on applying Machine Learning, specifically Reinforcement Learning, to optimize Automated Queue Management Systems. Prior to this, I earned Ph.D. candidate at the Edward S. Rogers Sr. Department of Electrical and Computer Engineering (ECE) at the University of Toronto, mentored by Pof. Kostas Plataniotis. My academic journey includes completing my master at Concordia University under the guidance of Prof. Arash Mohammadi. Email Google Scholar LinkedIn GitHub CV

Research

My research focuses on advancing autonomous artificial intelligence, targeting decision-making and interaction within real-world environments. This extends beyond the limitations of task-specific agents and involves substantial work in Reinforcement Learning and Active Inference, particularly addressing the critical areas of Transfer Learning, Uncertainty (Risk)-Aware Decision Making , Robust Loss Function Design, and Generative Models.

Highlighted Publications

See Google Scholar for more publications.

	Active Inference and Reinforcement Learning: A Unified Inference on Continuous State and Action Spaces under Partial Observability P Malekzadeh, KN Plataniotis Neural Computation, 2024 paper / webpage
	EX-DRL: Hedging Against Heavy Losses with EXtreme Distributional Reinforcement Learning P Malekzadeh, Z Poulos, J Chen, Z Wang, KN Plataniotis Preprint paper / webpage / code
	UaMB-SF: Uncertainty-aware transfer across tasks using hybrid Model-Based Successor Feature reinforcement learning P Malekzadeh, M Hou, KN Plataniotis Neurocomputing, 2023 paper / webpage
	A robust quantile huber loss with interpretable parameter adjustment in distributional reinforcement learning P Malekzadeh, KN Plataniotis, Z Poulos, Z Wang ICASSP , 2024 paper / code / webpage
	AKF-SR: Adaptive Kalman filtering-based Successor Representation P Malekzadeh, M Salimibeni, M Hou, A Mohammadi, KN Plataniotis Neurocomputing, 2022 paper / code / webpage
	UUaE: A Unified Uncertainty-aware Exploration combining epistemic and aleatory uncertainty P Malekzadeh, M Hou, KN Plataniotis ICASSP , 2023 paper / webpage
	MM-KTD: Multiple Model Kalman Temporal Differences for reinforcement learning P Malekzadeh, M Salimibeni, A Mohammadi, A Assa, KN Plataniotis IEEE Access, 2020 paper / code

Education

• Ph.D. in Electrical and Computer Engineering, University of Toronto, Canada (Sep. 2020- Jun. 2024)
• M.Sc. in Electrical and Computer Engineering, Concordia University, Canada (2018- 2020)
• B.Sc. in Electrical and Computer Engineering, Sharif University of Technology, Iran (2013- 2017)