About Me
I am a Ph.D. candidate 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. I am also doing a research internship at the Microsoft Research Asia (MSRA), working with Dr. Xingxing Zhang.
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
Research Summary
I develop principled methods and scalable infrastructure to enhance the capability and reliability of LLMs. My research combines deep learning theory with system-level optimization to improve model reliability and training data efficiency. Recent topics include:
- LLM Post-training (for coding agent): Preprint’26.
- Adversarial robustness and LLM jailbreak robustness: Preprint’26, ICLR’26, NeurIPS’25, ICLR’24.
- Model and data privacy: Preprint’24, ICLR’22a, ICLR’22b.
If you are interested in collaborating with me or discussing my research, please feel free to contact me through email.
News
- 04/2026: We released our new paper RefineRL: Advancing Competitive Programming with Self-Refinement Reinforcement Learning.
- 03/2026: We released our new paper Accelerating Suffix Jailbreak attacks with Prefix-Shared KV-cache.
- 01/2026: Our paper on LLM continuous adversarial training theory was accepted to ICLR 2026!
- 11/2025: I passed my Ph.D. Proposal Defense and officially became a Ph.D. candidate. Thanks to everyone who helped me during this journey!
- 09/2025: Our paper on LLM adversarial training theory was accepted to NeurIPS 2025!
- 08/2025: I accepted the invitation to serve as a reviewer for AISTATS 2026.
- 06/2025: I started an research internship at the Microsoft Research Asia (MSRA)!
Selected Publications [Full List] [Google Scholar]
* indicates co-first authors.
LLM Code Generation
- RefineRL: Advancing Competitive Programming with Self-Refinement Reinforcement Learning
[arXiv]
Shaopeng Fu, Xingxing Zhang, Li Dong, Di Wang, and Furu Wei
arXiv preprint 2026
Adversarial Robustness
Accelerating Suffix Jailbreak attacks with Prefix-Shared KV-cache
[arXiv] [Code]
Xinhai Wang*, Shaopeng Fu*, Shu Yang, Liangyu Wang, Tianhang Zheng, and Di Wang
arXiv preprint 2026Understanding and Improving Continuous LLM Adversarial Training via In-context Learning Theory
[Link]
Shaopeng Fu and Di Wang
ICLR 2026Short-length Adversarial Training Helps LLMs Defend Long-length Jailbreak Attacks: Theoretical and Empirical Evidence
[Link] [arXiv] [Video] [Code]
Shaopeng Fu, Liang Ding, Jingfeng Zhang, and Di Wang
NeurIPS 2025Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach
[OpenReview] [IEEE] [arXiv] [Video] [Code]
Shaopeng Fu and Di Wang
ICLR 2024
IEEE Transactions on Information Theory
Data/Model Privacy
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 2024Robust Unlearnable Examples: Protecting Data Against Adversarial Learning
[Link] [arXiv] [Video] [Code]
Shaopeng Fu, Fengxiang He, Yang Liu, Li Shen, and Dacheng Tao
ICLR 2022Knowledge Removal in Sampling-based Bayesian Inference
[Link] [arXiv] [Video] [Code]
Shaopeng Fu*, Fengxiang He*, and Dacheng Tao
ICLR 2022
Services
- Conference Reviewer: ICML (2022-2026) / ICLR (2022-2026) / NeurIPS (2021-2025) / AISTATS (2021, 2024-2026)
- Conference Committee: CCS 2024 (Artifact Evaluation) / AAAI 2025
- Journal Reviewer: Neurocomputing / TMLR / IEEE TIT / IEEE TPAMI / IEEE TNNLS / IEEE TCYB / Springer NPL
Selected Awards
- International Collegiate Programming Contest (ICPC)
- Gold Medal: Asia Regional Contest Shenyang Site (2018; Rank: 6/186)
- Silver Medals (3x): Asia-East Continent Final Xi’an Site (2018), Asia Regional Contest Qingdao Site (2017), and Asia Regional Contest Xi’an Site (2017)
- National Scholarship (2x): 2017 & 2018