About me
I am Zahidur Talukder, a Ph.D. candidate in the Department of Computer Science and Engineering at The University of Texas at Arlington, under the supervision of Dr. Mohammad Atiqul Islam. I earned my B.Sc. in Electrical and Electronic Engineering (EEE) from Bangladesh University of Engineering and Technology (BUET) in 2018, followed by an MBA from the Institute of Business Administration (IBA) at the University of Dhaka. I commenced my Ph.D. journey in the Fall of 2019.
My research is centered on the theoretical, empirical, and security aspects of algorithms and machine learning. Specifically, I focus on federated learning, where I have been working on efficient data and client handling. My contributions include developing self-regulating clients that can manage data-level errors and innovating new aggregation techniques for servers in federated learning environments.
I am deeply passionate about the applications of machine learning and algorithms, striving to create secure and efficient solutions. My work aims to address significant challenges in data privacy, AI sustainability, and fairness in heterogeneous federated learning systems. As a recognized Machine Learning and Systems Rising Star of 2024, I am dedicated to advancing the field and making impactful contributions.
News
October 2024: Our Paper “Hardware-Sensitive Fairness in Heterogeneous Federated Learning” got accepted in ACM TOMPECS-2024.
August 2024: Selected as Reviewer for ICLR 2024.
June 2024: Selected as Reviewer for NeurIPS 2024.
June 2024: Received a Certificate of Reviewing for contributing a review to ACM Performance Evaluation.
May 2024: Selected as one of the 2024 ML and Systems Rising Stars.
May 2024: Accepted as a graduate mentor for the I Engage Mentoring Program for Summer 2024.
Nov 2023: Our Paper “Enabling Low-Cost Server-Level Power Monitoring in Data Centers Using Conducted EMI” got accepted in Sensys23.
Feel free to reach out if you have any questions or would like to collaborate on research projects!