Justin Lee

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Contact: jhylee[at]umich[dot]edu

I am an incoming EECS Ph.D. student at the University of Michigan, starting in Fall 2026, where I will be advised by Dr. Qing Qu as part of the DeepThink Lab. Previously, I earned my B.S. in Computer Science and Engineering from The Ohio State University, where I was advised by Dr. Wei-Lun (Harry) Chao and mentored by Zheda Mai.

My current research interests broadly center on deep learning theory and generative modeling.

CV | Google Scholar | Github | LinkedIn

News

Jan 2026 Continual Unlearning for Diffusion accepted to ICLR 2026
Dec 2025 Selected as an Honorable Mention for the 2026 CRA Outstanding Undergraduate Researcher Award.

Publications

  1. ICLR
    Continual Unlearning for Text-to-Image Diffusion Models: A Regularization Perspective
    J Lee*, Z Mai*, J Yoo, C Fan, C Zhang, and 1 more author
    The Fourteenth International Conference on Learning Representations, 2026
    HTML PDF
  2. ICML Workshop
    An Empirical Exploration of Continual Unlearning for Image Generation
    J Lee*, Z Mai*, C Fan, and WL Chao
    In ICML 2025 Workshop on Machine Unlearning for Generative AI, 2025
    PDF
  3. Under Review
    TaxaAdapter: Coupling Vision Taxonomy Models with Diffusion for Fine-Grained Species Generation
    M Khurana, A Monsefi, J Lee, D Carlyn, J Chae, and 6 more authors
    Under Review, 2025
  4. NeurIPS
    MLLM-CompBench: A Comparative Reasoning Benchmark for Multimodal LLMs
    J Kii*, Z Mai*, J Lee, A Chowdhury, Z Wang, and 4 more authors
    In The Thirty-eight Conference on Neural Information Processing Systems, 2024
    HTML PDF
  5. TIGE
    Artificial Intelligence Advances Digital Pathomics for Confocal Endomicroscopy Diagnosis of Pancreatic Cysts
    A Abdelbaki, Z Li, TY Pan, J Lee, A Chowdhury, and 3 more authors
    Techniques and Innovations in Gastrointestinal Endoscopy, 2025
    PDF