About Me

Welcome to my home page 😊

My name is Arian (Persian: آریان ) – you can also call me Ari. I am a researcher in Electrical and Computer Engineering. I received my M.Sc. in Computer Engineering (Artificial Intelligence and Robotics) from the Department of Computer Engineering, Amirkabir University of Technology (Tehran Polytechnic). I also received my B.Sc. in Computer Engineering (Computer Hardware) from the CSE & IT Department of Shiraz University. My doctoral research in Electrical and Computer Engineering at Concordia University has focused on reinforcement learning and restless bandit methods for scheduling, where I passed the PhD Comprehensive Examination in 2025.

I find great fulfillment in exploring the intersection of theoretical principles in machine and deep learning with their diverse applications. My master's research centered on statistical signal processing, specifically modeling space-time-frequency representations in image processing. I explored image decomposition techniques to uncover latent representations across new domains, coupled with the statistical analysis of the resulting coefficients. My research interests include statistical modeling, optimization, and reinforcement learning.

I am open to PhD positions in reinforcement learning, statistical signal processing, and image/medical image processing.

News

  • [2026-09]: Applying for PhD admission for Winter/Fall 2027 in reinforcement learning, statistical signal processing, and image/medical image processing.
  • [2026-01]: Conference paper published — A Novel Whittle Index-Based Scheduling for Age of Information Minimization in IoT Networks — IEEE SmartIoT 2025.
  • [2025-02]: Passed the PhD Comprehensive Exam, Department of Electrical and Computer Engineering, Concordia University.
  • [2023-09 – 2024-04]: Research Assistant at Mila – Quebec AI Institute.
  • [2022-09 – 2026-04]: Doctoral research, Department of Electrical and Computer Engineering, Concordia University.
  • [2022-03]: Journal paper published — A Novel Gaussian-Copula Modeling for Image Despeckling in the Shearlet Domain — Signal Processing.
  • Journal paper published — A Novel Statistical Approach for Multiplicative Speckle Removal Using t-Location-Scale and Non-Subsampled Shearlet Transform — Digital Signal Processing.