About

Hi, this is Wu-Chengpei, I am pursuing my PhD at the Graduate School of Advanced Science and Engineering, Hiroshima University, under the supervision of Yang Lou and co-supervision of Yi Yu. My research interests include machine learning and graph representation learning. Recently, my work has primarily focused on unsupervised graph representation learning, including topics such as graph contrastive learning. Previously, I explored deep learning methods for efficient and accurate robustness estimation in complex networks. In addition, I am also interested in robust machine learning, generative modeling, and large language models.

I also maintain a personal blog here, where I write about topics related to machine learning.

News

[03/2026] Awarded the JST BOOST Fellowship (Next-Generation AI Fellow) at Hiroshima University.
[08/2025] Paper (co-authored) accepted by IEEE Computational Intelligence Magazine.
[04/2025] Two papers (co-authored) accepted by CVPR 2025 and IJCAI 2025.
[06/2024] Paper accepted by IEEE Transactions on Cybernetics.
[10/2023] Awarded the National Scholarship for Graduate Students by the Chinese Ministry of Education.
[07/2023] Paper accepted by IEEE Transactions on Circuits and Systems I: Regular Papers.
[06/2023] Paper accepted by IEEE International Conference on Systems, Man, and Cybernetics (SMC) 2023.

Selected Publications

[1] Chengpei Wu, Yang Lou, Junli Li, Lin Wang, Shengli Xie, and Guanrong Chen, “A Multitask Network Robustness Analysis System Based on the Graph Isomorphism Network.” IEEE Transactions on Cybernetics (TCYB).

[2] Chengpei Wu, Yang Lou, and Junli Li “Pyramid Pooling-Based Local Profiles for Graph Classification” IEEE International Conference on Systems, Man, and Cybernetics (SMC) October 1-4, 2023, Maui, Hawaii, USA.

[3] Chengpei Wu, Yang Lou, Lin Wang, Junli Li, and Guanrong Chen, “SPP-CNN: An Efficient Framework for Network Robustness Prediction,” IEEE Transactions on Circuits and Systems I: Regular, doi:10.1109/TCSI.2023.3296602.

[4] Yang Lou, Chengpei Wu, Junli Li, Lin Wang, and Guanrong Chen, “Network Robustness Prediction: Influence of Training Data Distributions,” IEEE Transactions on Neural Networks and Learning Systems, doi:10.1109/TNNLS.2023.3269753.

Honors and Awards

Outstanding Graduate, Chengdu University (2021).
Academic Scholarship, Sichuan Normal University (2022).
National Scholarship, Sichuan Normal University (2023).
Merit Student, Sichuan Normal University (2023).
Outstanding Graduate from Sichuan Normal University and Sichuan Province (2024).

Educations

2017.09 - 2021.06, Undergraduate, Chengdu University, Chengdu.
2021.09 - 2024.06, Master, Sichuan Normal University, Chengdu.

Academic Services

Reviewer for IEEE Transactions on Neural Networks and Learning Systems (TNNLS), IEEE Transactions on Cybernetics (TCYB), Reliability Engineering and System Safety (RESS), The ACM Web Conference (WWW), etc.

I am looking into:

Analysis and Statistics: Analysis I, All of Statistics.
Generative Modeling: Flow Matching Guide and Code, An Introduction to Flow Matching and Diffusion Models.
Computational Learning Theory: Computational Learning Theory - University of Oxford.
Robust Machine Learning: Robustness in Machine Learning.
Deep Reinforcement Learning: CS 224R - Stanford University

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