About Me
Welcome to my home page 😊
My name is Arian (Persian: آریان ) – you can also call me Ari. I am a Ph.D. student and research assistant in Departement of Electrical and Computer Engineering at Concordia University. 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. 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. In terms of Methodology, my previous work was grounded in Applied Machine Learning and Deep Learning. Currently, my research focuses on statistical modeling, optimization, and reinforcement learning. In terms of Application, I have worked across diverse domains, including medical image processing, wireless communication, and time series analysis.
News
- [2026-01]: A Novel Whittle Index-Based Scheduling for Age of Information Minimization in IoT Networks was published in Conference IEEE SmartIOT 2025.
- [2025-02]: Successful Completion of Ph.D. Comprehensive Exam.
- [2024-09]: Continuing Ph.D. under the co-supervision of Dr. Y.R. Shayan and Dr. D. Qiu.
- [2024-04]: Left the IMPACT Lab to focus on the theoretical aspects of optimization and reinforcement learning.
- [2022-09]: Started Ph.D. studies at the IMPACT Lab, Departement of Electrical and Computer Engineering, Concordia University, under the supervision of Dr. H. Rivaz
- [2022-03]: A Novel Gaussian-Copula modeling for image despeckling in the shearlet domain was published in Journal of Signal Processing.
- [2020-12]: A novel statistical approach for multiplicative speckle removal using t-locations scale and non-sub sampled shearlet transform was published in Journal of Digital Signal Processing.



