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Gang Yan (燕刚)

Full Professor

Jilin University

📧 gyan8@jlu.edu.cn

📍 Changchun, Jilin, China

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About Me

I received my Ph.D. in Electrical and Computer Engineering from the State University of New York at Binghamton in 2023. Prior to that, I earned an M.S. (2019) and a B.S. (2016) in Statistics from Nankai University (China). In 2024, I served as a postdoctoral scholar at the University of California, Merced, where I further advanced my research expertise.

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Research Interests

My research centers on high-performance network optimization, cloud and edge computing, distributed machine learning, and federated learning. A key focus is addressing security challenges in distributed systems, with an emphasis on designing robust attack mitigation and defense strategies. I strive to advance the efficiency, scalability, and resilience of modern computing infrastructures through innovative and interdisciplinary approaches.

Join NODI Lab.

NODI Lab. invites three Ph.D. students to begin in Fall 2026. Research themes include high‑performance networking, edge and cloud computing, distributed and federated learning, and secure distributed systems. Applicants should hold or expect a Master’s degree in Computer Science, Electrical Engineering, Statistics, or a related field. Strong programming skills and a solid mathematics foundation are required. To apply, email your CV, undergraduate and graduate transcripts, and research statement to gyan8@jlu.edu.cn.

NODI Lab. also welcomes applications for postdoctoral researchers and tenure‑track professors. Candidates should hold a Ph.D. in a relevant area. To apply, send your CV and a cover letter to the same email.

Recent News

[December 2024] [Position] I will join Jilin University (China), as a full professor starting in 2025.

[November 2024] [Service] I will serve as the heavy Program Committee for USENIX ATC 2025.

[August 2024] [News] Congratulations to my PhD advisor, Prof. Jian Li, on receiving the prestigious NSF CAREER Award!

[August 2024] [Paper] Our paper "Straggler-Resilient Decentralized Learning via Adaptive Asynchronous Update" accepted to MobiHoc 2024.

[June 2024] [Paper] Our paper "Enhancing Model Poisoning Attacks to Byzantine-Robust Federated Learning via Critical Learning Periods" accepted to RAID 2024.

[June 2024] [Service] I will serve as a Program Committee (PC) member for AAAI 2025.

[May 2024] [Paper] Our paper "FedRoLA: Robust Federated Learning Against Model Poisoning via Layer-based Aggregation" accepted to ACM KDD 2024.