Yanbo Fan
Scholar

Yanbo Fan

Google Scholar ID: OlOqHyUAAAAJ
Nanjing University
AI SafetyAIGC
Citations & Impact
All-time
Citations
3,001
 
H-index
30
 
i10-index
45
 
Publications
20
 
Co-authors
15
list available
Resume (English only)
Academic Achievements
  • - Invited as an Area Chair of ICLR 2026
  • - One paper about Digital Avatar conditionally accepted to Siggraph Asia 2025
  • - Two papers about Digital Avatar accepted to ICCV 2025
  • - Five papers about Digital Avatar accepted to CVPR 2025
  • - Will serve as an Area Chair of ICME 2025
  • - One paper about adversarial examples accepted to Pattern Recognition
  • - Invited as an Area Chair of ICLR 2025
  • - Invited as an Area Chair of WACV 2025
  • - One paper about text-to-texture accepted to ECCV 2024
  • - One paper about adversarial training accepted to IJCV
  • - One paper about motion generation accepted to NeurIPS 2023
  • - One paper about Fast Adversarial Training accepted to TIP
Research Experience
  • - Senior Research Scientist at Ant Research, Oct. 2023 to Jun. 2025
  • - Senior Research Scientist at Tencent AI Lab, Jul. 2018 to Oct. 2023
  • - Tenure-Track Associate Professor at Nanjing University (Suzhou Campus), joining in July 2025
Education
  • - PhD: National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 2013-2018, Supervisors: Prof. Bao-Gang Hu and Prof. Ran He
  • - Visiting Student: Computer Vision and Machine Learning Lab (CVML), University at Albany, State University of New York, 2016-2017, Supervisor: Prof. Siwei Lyu
  • - BS: Hunan University, June 2013, Major: Computer Science and Technology
Background
  • Research Interests: Trustworthy and Generative AI. Professional Field: Intelligence Science and Technology. Brief Introduction: Currently, a Tenure-Track Associate Professor at the School of Intelligence Science and Technology, Nanjing University (Suzhou Campus).
Miscellany
  • The research group is always looking for outstanding students to join, including doctoral, master's, and undergraduate students. Each student receives one-on-one research guidance, and excellent students are actively recommended for internships at major companies.