
I am a fourth year PhD student in Electrical Engineering at the Universoty of Southern California, working with Prof. Salman Avestimehr. My research focuses on the intersection of federated learning and graph machine learning. Recently, I have a keen interest in generative flow networks and conformal prediciton. I have been selected as a 2025 North America Finalist at the Qualcomm Innovation Fellowship.
Research Topics
My Contributions +
Recent News
- February 2025 - Became a finalist at the 2025 Qualcomm Innovation Fellowship.
- February 2025 - Awarded with Travel Grant for the SIAM-SDM'25 conference, a top-tier conference in ML & data-mining..
- January 2025 - Became a semi-finalist at the 2025 Qualcomm Innovation Fellowship .
- December 2024 - FedGrAINS, first GFlowNet paper to improve subgraph federated learning has been accepted to the SIAM-SDM'25 conference. Preprint is available in this link.
Ultimately, I am driven by a deep interest in understanding and defining intelligence, whether it's in animals or artificial systems. While I'm excited about the potential of AI, I'm also mindful of its limitations and potential pitfalls – I'm definitely not a technosolutionist.
Before my current role, Before joining USC, I received my MSc and BSc degrees from the Electrical Engineering at Bilkent University as a Senior Researcher in 2018 and 2020 respectively.