Yuanhe Guo is a Ph.D. student in Computer Science advised by Professor Hongyi Wen in the MAPS Research Group. Prior to that, he earned his B.S. degree in Data Science from NYU Shanghai and graduated with Major Honors in Computer Science, Data Science, and Engineering. Currently, his research interest lies in discrete diffusion models. He is also interested in investigating the inverse problem of creative content rendering: reconstructing latent, structured representations from high-level rendered outputs using deep generative models.
Publications
- Guo Yuanhe, Linxi Xie, Zhuoran Chen, Kangrui Yu, Ryan Po, Guandao Yang, Gordon Wetztein and Hongyi Wen. “ImageGem: In-the-wild Generative Image Interaction Dataset for Generative Model Personalization”. Proceedings of the International Conference on Computer Vision, ICCV 2025.
- Guo Yuanhe, Haoming Liu and Hongyi Wen. “GEMRec: Towards Generative Model Recommendation.” Proceedings of the 17th ACM International Conference on Web Search and Data Mining (2023).
Research Interests
- Personalized Image Generation
- Multi-Modality Diffusion Models and LoRAs
- Representation Learning
- Model Interpretability