Zepeng Zhang

PhD Student at EPFL

Email (zepeng.zhang@epfl.ch) Wechat (zpzhang717)

[CV]

About Me

I am a PhD student at École Polytechnique Fédérale de Lausanne (EPFL). I work in the Intelligent Maintenance and Operations Systems (IMOS) Lab under the supervision of Prof. Olga Fink. Previously, I received my master's degree at ShanghaiTech University and B.Eng. degree from Wuhan University (WHU). I also had the opportunity to visit Peking University (PKU) and City University of HongKong (CityU) as a research intern.

My current research focuses on Graph Machine Learning and Algorithmic Reasoning.

News

• [Sep. 2024] One paper has been accepted by APSIPA ASC 2024.
• [Sep. 2024] The paper “Graph Neural Networks with Adaptive Structures” has been accepted by the IEEE Journal of Selected Topics in Signal Processing.
• [Aug. 2024] New preprint entitled "Algorithm-Informed Graph Neural Networks for Leakage Detection and Localization in Water Distribution Networks" has been released.
• [May 2024] The paper “Accelerating Quadratic Transform and WMMSE” has been accepted by the IEEE Journal on Selected Areas in Communications.
• [Apr. 2024] One paper has been accepted by GSP 2024.
• [Nov. 2023] New preprint entitled "Discerning and Enhancing the Weighted Sum-Rate Maximization Algorithms in Communications" has been released.
• [Sep. 2023] Begin PhD study in EPFL.
• [Feb 2023] One paper has been accepted by ICASSP 2023.
• [June 2022] New preprint entitled "Towards Understanding Graph Neural Networks: An Algorithm Unrolling Perspective" has been released.
• [Sep. 2021] Our paper has been selected as the Best Student Paper Award Finalist in IEEE SPAWC 2021!
• [Aug. 2020] One paper has been accepted by Asilomar 2020.

Education & Experiences

• Electrical Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
  Sep. 2023 -

• National Institute of Health Data Science, Peking University, Beijing, China
  Feb. 2023 - April 2023

• School of Information Science and Technology, ShanghaiTech University, Shanghai, China
  Dec. 2019 - June 2023
  Dissertation: Optimization-Induced Graph Neural Networks

• Department of Measuring & Control Technology and Instrumentations, School of Electronic Information, Wuhan University, Wuhan, China
  Sept. 2016 - June 2020

• Department of Electronic Engineering, College of Engineering, City University of HongKong, HongKong
  July 2019 - Sept. 2019

Selected Publications

• ASGNN: Graph Neural Networks with Adaptive Structure
  Zepeng Zhang, Songtao Lu, Zengfeng Huang, and Ziping Zhao
  IEEE Journal of Selected Topics in Signal Processing
  [paper]

• Discerning and Enhancing the Weighted Sum-Rate Maximization Algorithms in Communications
  Zepeng Zhang, Ziping Zhao, Kaiming Shen, Daniel P. Palomar, and Wei Yu
  [paper]

• Weighted Sum-Rate Maximization for Multi-Hop RIS-Aided Multi-User Communications: A Minorization-Maximization Approach
  Zepeng Zhang and Ziping Zhao
  IEEE SPAWC 2021 (Best Student Paper Award Finalist)
  [paper]

Teaching

• Teaching Assistant for CIVIL 425: Machine learning for predictive maintenance applications | 2023-24 Fall, EPFL.
• Teaching Assistant for CS 182: Introduction to Machine Learning | 2021-22 Fall, ShanghaiTech.
• Teaching Assistant for SI 231: Matrix Analysis and Computations | 2020-21 Spring, 2021-2022 Spring, ShanghaiTech.

Awards & Honors

Contests

• 1^st prize of 2018 RoboCup China Open 2018

• 1^st prize of 2018 Asia and Pacific Mathematical Contest in Modeling 2018

• 3^rd prize of 2018 The Chinese Robot Skills Competitions 2018

• 1^st prize of 2017 The Chinese Mathematics Competitions, Hubei Prov. 2017

Scholarships

• Yu Gang Scholarship (Top 1%, Rank 1^st out of the department), WHU, 2018-19

• SAMSUNG Scholarship (Top 1%, Rank 1^st out of the department), WHU, 2017-18

• The First Prize Scholarship (Top 5%), WHU, 2017-18, 2018-19

• The Second Prize Scholarship (Top 15%), WHU, 2016-17

Academic Service

• Conference Reviewer: ICLR 2025, NeurIPS 2024; LOG 2024, AISTATS 2024,2023; ICASSP 2025, 2024; WWW 2023; ECAI 2024; IEEE MLSP 2023; TGL-NeurIPS 2023,2022.
• Journal Reviewer: IEEE Open Journal of Signal Processing, Neurocomputing.

Personal

In my free time, I enjoy traveling, hiking, reading, practicing guitar, and hip-hop music. Besides, I like watching TV shows (my favorites are Vikings, Breaking Bad, Prison Break, etc.).