About Me
I’m Borna, a machine learning researcher and engineer with over four years of experience in both industry and academia. Currently, I work as an algorithm designer at Cognitive Systems Corp. where I design and develop representation learning solutions for motion sequential data in WiFi sensing applications. I recently graduated in 2024 with a Master’s degree in Computer Science from York University, where I worked with Dr. Hina Tabassum in the NGWN research lab. There, I led research on WiFi sensing, focusing on self-supervised learning and lightweight compression networks.
Research Interests
My research centers on building representation learning frameworks that generalize across tasks without relying on supervised signals. I have a strong interest in unsupervised and self-supervised learning to address challenges such as low-labeled data and out-of-distribution detection.
Recently, my work has focused on contrastive learning and predictive coding frameworks for time-series data. As part of my master’s research, I developed a self-supervised learning framework for Channel State Information (CSI) time-series data from WiFi signals, with in indoor human activity recognition (HAR) and other WiFi sensing applications.
News
October 2024: Our work “Context-Aware Predictive Coding: A Representation Learning Framework for WiFi Sensing” was accepted to be presented at the NeurIPS 2024 5th Workshop on Self-Supervised Learning: Theory and Practice in Vancouver, Canada, in December 2024.
September 2024: Our work “Context-Aware Predictive Coding: A Representation Learning Framework for WiFi Sensing” was published in the top-tier IEEE Open Journal of the Communications Society.
August 2024: Started a new position as an Algorithm Designer at Cognitive Systems Corp. working on cutting-edge WiFi sensing technologies!
July 2024: Defended my master’s thesis, “Robust Representation Learning Solutions for Wireless Sensing Applications,” at York University with 1 Conference paper published and 1 Journal article submitted and got nominated for the thesis prize!
July 2024: Participated in the 2024 CIFAR Deep Learning Reinforcement Learning (DLRL) summer school and presented a poster on “Self-Supervised Learning for WiFi Sensing”.
June 2024: Participated in Leader’s of Tomorrow Workshop at Toronto Metropolitan University and presented a poster on “Self-Supervised Learning for WiFi Sensing”.
April 2024: Received the York University Academic Excellence Fund.
January 2024: Our work “RSCNet: Dynamic CSI Compression for Cloud-Based WiFi Sensing” was accepted to the top-tier conference, IEEE International Conference on Communications (ICC), which will be held in Denver, CO, USA, in June 2024.
September 2023: Attended the IEEE PIMRC 2023 conference in Toronto, Canada and presented a poster on “Wi-Fi Sensing and CSI Compression using Deep Learning” at the Frontier Networking Systems (FNS).