Fengpeng Li
Fengpeng Li

Fengpeng Li

PostDoc Research Fellow

King Abdullah University of Science and Technology (KAUST)

Research Interests

  • trustworthy machine learning(LLM, VLM, Agent, and Diffusion Models)
  • Trustworthy AI (AIGC and DeepFake Detection)
  • GeoAI (Intelligent Method for Geosciences)

Last Updated: 2026-05

About Me

I am Fengpeng Li, currently a post-doc Research Fellow at Prada Lab, [King Abdullah University of Science and Technology (KAUST)], (https://www.kaust.edu.sa/), advised by Prof. Di Wang). Prior to that, I earned my BS degree in Remote Sensing Science and Technology and Mphil degree of Computer Science and Technology from China University of Geosciences(Wuhan) under the supervison of Prof. Lizhe Wang, and my PhD degree in Computer Science from IOTSC of University of Macau, advised by Prof. Jiantao Zhou. I also work closely with Mr. Kemou Li, Dr. Qizhou Wang, Prof. Haiwei Wu, and Prof. Bo Han.

I am currently focusing on machine unlearning for LLMs, with an emphasis on theoretical foundations. I am also interested in broader topics in trustworthy foundation models, machine learning, and AI security. I am always open to collaboration or exchanging ideas on related topics.

I am looking for visiting PhD opportunity. Please feel free to contact me about any potential openings :)

News

  • 2026-03 Our team wins the 6th place (6/511) at the NTIRE @ CVPR 2026: Robust AI-Generated Image Detection in the Wild Challenge.
  • 2026-02 One paper on image forensics accepted to CVPR 2026 Highlight. See you in Denver!
  • 2026-01 Two papers on LLM unlearning and diffusion model concept erasure accepted to ICLR 2026. See you in Rio de Janeiro!
  • 2025-06 One paper on adversarial training accepted to IEEE TIFS.
  • 2025-06 Pass my PhD qualifying exam.
  • 2025-05 One paper on learning with noisy labels accepted to IJCV.
  • 2025-02 One paper on font watermarking accepted to IEEE TMM.
  • 2025-01 Start remote research at TMLR Group with Dr. Qizhou Wang and Prof. Bo Han.
  • 2024-09 One paper on adversarial training accepted to NeurIPS 2024.
  • 2024-09 Our team wins the championship (1/706) at the Global Multimedia Deepfake Detection Challenge (Image Track) at the 2024 Inclusion Conference on the Bund.
  • 2024-08 Start my PhD journey at the University of Macau.
  • 2023-12 One paper on learning with noisy labels accepted to AAAI 2024 Oral (2.2%).

Selected Publications

* = Equal Contribution

  2. Editprint: General Digital Image Forensics via Editing Fingerprint with Self-Augmentation Training CVPR-26 Highlight
    Editprint: General Digital Image Forensics via Editing Fingerprint with Self-Augmentation Training
    Haiwei Wu*, Kemou Li*, Yuanman Li, Jiantao Zhou
    Conference on Computer Vision and Pattern Recognition (CVPR), 2026
    Code CCF A Highlight
  3. LLM Unlearning with LLM Beliefs ICLR-26
    LLM Unlearning with LLM Beliefs
    Kemou Li, Qizhou Wang, Yue Wang, Fengpeng Li, Jun Liu, Bo Han, Jiantao Zhou
    International Conference on Learning Representations (ICLR), 2026
    PDF CCF A

Awards & Honors

Professional Services

Organizing Committee

Session Chair

APSIPA ASC 2024, Dec. 3-6, Macao, China

Conference Reviewer

NeurIPS 2025-2026 ICLR 2026 ICML 2026 CVPR 2026 ECCV 2026 ACM MM 2026 APSIPA ASC 2024-2025

Journal Reviewer

IEEE TIFS Knowledge-Based Systems

Teaching Experience

Teaching Assistant

University of Macau

I have supported both postgraduate (PG) and graduate (G) courses in artificial intelligence, machine learning, multimedia, and image processing.

CISC8001 PG
Spring 2026

Principles of Artificial Intelligence

GEST1009 G
Fall 2025

Multimedia Technology in Modern Society

CISC7202 PG
Spring 2025

Tools for Machine Learning

CISC7014 PG
Fall 2024

Advanced Topics in Computer Science (Image Processing and Pattern Recognition)