Yifan Yuan, PhD, is an Assistant Professor and Master's Supervisor at the School of Artificial Intelligence, Shenzhen University. He received his Ph.D. in Computer Science and his Bachelor of Science in Physics from Fudan University in 2019 and 2025, respectively, under the supervision of Professor Junping Zhang.
His main research interests include AIGC, large models, trustworthy image and video editing, and multimodal content generation. He focuses on controllability and consistency issues in editing tasks, such as editing accuracy, semantic consistency, identity preservation, and the illusion problem in large models. He also explores the potential of generative models in high-value vertical scenarios such as virtual try-on and digital human modeling.
He has participated in multiple research projects, including those funded by the National Natural Science Foundation of China, the National Key Research and Development Program of China, and the Ministry of Education. He also serves as a reviewer for papers in several journals and conferences, including IEEE TIV, CVPR, ICML, AAAI, and ACM MM.
Education Background:
2019.09-2025.03, Fudan University, Computer Science and Technology, PhD in Science
2015.09-2019.06, Fudan University, Physics, Bachelor of Science
Research Interests
AIGC, Large Models, Generative Models, Image and Video Generation/Editing
📢 Recruitment Information:
Our research group recruits Master's and Undergraduate students year-round. Students interested in generative artificial intelligence, image editing, multimodal large models, and content generation fairness are welcome to contact me via email: yifanyuan@szu.edu.cn. The email subject should be "University-Name-Master's/Undergraduate/RA". Please attach your CV to the email, briefly describing your motivation for applying, academic ranking, and research experience. You can also include your creative ideas, unique strengths, and even your quirky personality!
What You Can Gain?
1. A Free Research Environment: I earned my PhD at 23, am young and energetic, hold an MBTI ESFP certification, am humorous, meticulous, and responsible, and excel at providing students with comprehensive support in learning, research, interests, and life. The research group has a relaxed and free atmosphere; push is not encouraged! My motto is "Happiness First," and I believe that passion can withstand the test of time. A genuine passion can help us produce impactful work, therefore I encourage and support you in finding a research direction that interests you.
2. One-on-One Mentoring: A customized support path will be provided based on your development stage. If you are more senior, we will work together to hone your leadership and mentorship skills; if you are more junior, I will provide more hands-on technical training and research companionship. No matter what stage you are at, I hope to grow and enjoy life with you!
3. High-Quality Research Output as a Goal: We encourage publication in Nature sub-journals and CCF A-level conferences and journals, providing full guidance without trying to claim first authorship.
4. Emphasis on both research and application: You will have the opportunity to explore the real-world applications of large-scale models and connect with resources from companies such as Tencent, Alibaba, ByteDance, SenseTime, China Telecom, and China Mobile.
5. Diverse development: We encourage internships and industry-university collaborative training programs, overseas academic exchanges, and participation in conferences and networking events. I'm a Gen Z, around your age, so my mentorship will be more like a friendly approach. Besides focusing on solid scientific research, I hope we can also explore life and see the world together, visit art exhibitions, concerts, and combine art and technology to create something cool! I look forward to having someone passionate about research and innovation join my team to jointly promote the development of intelligent vision and creative technologies!
Representative scientific research results
[1]Y. Yuan, G. Yang, J. Z. Wang, H. Zhang, H. Shan, FY Wang and J. Zhang. Dissecting and Mitigating Semantic Discrepancy in Stable Diffusion for Image-to-Image Translation. IEEE/CAA Journal of Automatica Sinica, 2025, 12(4): 705-718. [DOI: 10.1109/JAS.2024.124800] SCI IF: 15.3, Top 1 (Q1)
[2]Y. Yuan*, S. Ma*, H. Shan, and J. Zhang. DO-FAM: Disentangled Non-Linear Latent navigation for Facial Attribute Manipulation. IEEE International Conference on Acoustics, Speech and Signal Processing, 2023.
[3]Y. Yuan, S. Ma, and J. Zhang. VR-FAM: Variance-Reduced Encoder with Nonlinear Transformation for Facial Attribute Manipulation. IEEE International Conference on Acoustics, Speech and Signal Processing, 2022: 1755-1759.
[4] F. Xu, Y. Yuan, J. Zhang, and J. Z. Wang. Chapter 7: High-Speed Joint Learning of Action Units and Facial Expressions. Modeling Visual Aesthetics, Emotion, and Artistic Style. Berlin, Heidelberg: Springer Berlin Heidelberg, 2023.
[5] F. Xu,Y. Yuan, J. Zhang, and J. Z. Wang. Chapter 8: ExpressionFlow: A Microexpression Descriptor for Efficient Recognition. Modeling Visual Aesthetics, Emotion, and Artistic Style. Berlin, Heidelberg: Springer Berlin Heidelberg, 2023.
[6] G. Li,Y. Yuan, X. Ben, and J. Zhang. Spatiotemporal attention network for microexpression recognition. Journal of Image and Graphics, 2020, 25(11): 2380-2390. [DOI: 10.11834/jig. 200325] Representative Research Projects [1] National Natural Science Foundation of China, Research on Deep Learning Based on Graph Convolutional Neural Network and Decoupling Learning, Project No. 62176059, 2022.01-2025.12, Completed, Participant [2] National Key Research and Development Program (13th Five-Year Plan), Key Theories and Technologies of Human-Machine Collaboration Based on Teaching and Imitation Learning, Project No. 2018YFB1305104, 2019.06-2022.05, Completed, Participant [3] Ministry of Education Project, Research on Planning of Human-Machine Collaborative Hybrid Enhanced Intelligent Algorithm, 2020.01-2021.12, Completed, Participant [4] Horizontal Project, Shanghai Central Meteorological Observatory, Development Project of Heavy Precipitation Forecasting Technology Based on Machine Learning, 2020.03-2021.04, Completed, Participant
[5] Shanghai Science and Technology Innovation Action Plan, Automatic Correction Technology of Numerical Simulation Error Based on Big Data Deep Learning, Project No. 18DZ1200404, 2018.04-2021.03, Completed, Participant
[6] National Natural Science Foundation of China, Research on Multimodal and Multi-view Pedestrian Gait Recognition Based on Machine Learning, Project No. 61673118, 2017.01-2020.12, Completed, Participant
