About Me

I am a Ph.D. student at the Provable Responsible AI and Data Analytics (PRADA) Lab at the King Abdullah University of Science and Technology (KAUST), advised by Prof. Di Wang.

Before that, I was an algorithm engineer at the trustworthy AI research group at JD Explore Academy, JD.com, Inc. I received MPhil in Computer Science from The University of Sydney, advised by Prof. Dacheng Tao, and B.Sc in Mathematics from the South China University of Technology, advised by Prof. Chuhua Xian.

Contact
shaopeng.fu@kaust.edu.sa
shaopengfu15@gmail.com

Pinned
PRADA Lab is looking for Postdocs/PhDs/Interns. Please checkout this page.

Research Interests

My research lies in trustworthy AI. I am interested in using mathematical principles to identify and mitigate security and privacy risks in real-world machine learning systems. Currently, I am working on:

  • Adversarial Robustness of Pre-trained Models
  • Privacy-preserving Ability of Pre-trained Models

News

- 08/2023: I started my Ph.D. journey at the [King Abdullah University of Science and Technology](https://www.kaust.edu.sa/)! - 08/2023: I accepted the invitation to serve as a reviewer for [ICLR 2024](https://openreview.net/group?id=ICLR.cc/2024/Conference). - 05/2023: I started a research internship at the [PRADA Lab](http://www.pradalab.org/) @ [KAUST](https://www.kaust.edu.sa/), hosted by [Prof. Di Wang](https://shao3wangdi.github.io/)! - 03/2023: I accepted the invitation to serve as a reviewer for [NeurIPS 2023](https://openreview.net/group?id=NeurIPS.cc/2023/Conference). - 12/2022: I accepted the invitation to serve as a reviewer for [ICML 2023](https://openreview.net/group?id=ICML.cc/2023/Conference). - 07/2022: I accepted the invitation to serve as a reviewer for [ICLR 2023](https://openreview.net/group?id=ICLR.cc/2023/Conference). - 03/2022: I accepted the invitation to serve as a reviewer for [NeurIPS 2022](https://openreview.net/group?id=NeurIPS.cc/2022/Conference). - 01/2022: Two papers were accepted to [ICLR 2022](https://openreview.net/group?id=ICLR.cc/2022/Conference)!

Selected Publications [Full List] [Google Scholar]

* indicates co-first authors.

  • Pre-trained Encoder Inference: Revealing Upstream Encoders In Downstream Machine Learning Services
    [arXiv] [Code]
    Shaopeng Fu, Xuexue Sun, Ke Qing, Tianhang Zheng, and Di Wang
    arXiv preprint 2024

  • Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach
    [Link] [arXiv] [Video] [Code]
    Shaopeng Fu and Di Wang
    ICLR 2024

  • Robust Unlearnable Examples: Protecting Data Against Adversarial Learning
    [Link] [arXiv] [Video] [Code]
    Shaopeng Fu, Fengxiang He, Yang Liu, Li Shen, and Dacheng Tao
    ICLR 2022

  • Knowledge Removal in Sampling-based Bayesian Inference
    [Link] [arXiv] [Video] [Code]
    Shaopeng Fu*, Fengxiang He*, and Dacheng Tao
    ICLR 2022

Services

  • Conference Reviewer: ICML (2022, 2023, 2024) / ICLR (2022, 2023, 2024, 2025) / NeurIPS (2021, 2022, 2023, 2024) / AISTATS (2021, 2024, 2025)
  • Conference Committee: CCS 2024 (Artifact Evaluation) / AAAI 2025
  • Journal Reviewer: IEEE TPAMI / IEEE TCYB / Springer NPL

Teaching

  • Teaching Assistant of CS 229: Machine Learning, Spring 2024 @ KAUST

Selected Awards

  • International Collegiate Programming Contest (ICPC)
    • The ICPC Asia-East Continent Final Xi’an Site, Silver Medal, 2018
    • The ICPC Asia Regional Contest Qingdao Site, Silver Medal, 2018
    • The ICPC Asia Regional Contest Shenyang Site, Gold Medal (Rank: 6/186), 2018
    • The ACM-ICPC Asia Regional Contest Xi’an Site, Silver Medal, 2017
  • National Scholarship, Ministry of Education of P.R. China, 2017 & 2018