Zahidur Talukder

Zahidur Talukder

Ph.D. Candidate in Department of Computer Science at The University of Texas at Arlington

Sitemap

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Pages

Posts

Future Blog Post

less than 1 minute read

Published:

This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

publications

Efficient Federated Learning with Self-Regulating Clients

Published in ACM SIGMETRICS / IFIP PERFORMANCE 2022, 2022

Proposed a self regulating clients to save both local computation and communication

Recommended citation: Talukder, Zahidur, and Mohammad A. Islam. "Efficient Federated Learning with Self-Regulating Clients." https://www.researchgate.net/profile/Zahidur-Talukder-2/publication/361939981_FedSRC_Efficient_Federated_Learning_with_Self-Regulating_Clients/links/62cda209c276426014a9677c/FedSRC-Efficient-Federated-Learning-with-Self-Regulating-Clients.pdf

Computationally Efficient Auto-Weighted Aggregation for Heterogeneous Federated Learning

Published in IEEE International Conference on Edge Computing and Communications (EDGE), 2022

Proposed an auto weighted aggregation techniques for FL

Recommended citation: Z. Talukder and M. A. Islam, "Computationally Efficient Auto-Weighted Aggregation for Heterogeneous Federated Learning," 2022 IEEE International Conference on Edge Computing and Communications (EDGE), 2022, pp. 12-22, doi: 10.1109/EDGE55608.2022.00015. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9860312

Enabling Low-Cost Server-Level Power Monitoring in Data Centers Using Conducted EMI

Published in SenSys '23: Proceedings of the 21st ACM Conference on Embedded Networked Sensor Systems, 2023

Proposed an auto weighted aggregation technique for FL

Recommended citation: Gupta, Pranjol Sen and Talukder, Zahidur and Abir, Tasnim Azad and Nguyen, Phuc and Islam, Mohammad A., "Enabling Low-Cost Server-Level Power Monitoring in Data Centers Using Conducted EMI," Proceedings of the 21st ACM Conference on Embedded Networked Sensor Systems, 2023, pp. 237–250, doi: 10.1145/3625687.3625801. https://dl.acm.org/doi/abs/10.1145/3625687.3625801

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

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