Kuan-Chieh (Jackson) Wang

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Bio

Hi! I am a Research Scientist at Snap Research in Palo Alto, where I lead a team focused on personalization in generative models. We are broadly interested in tailoring generative models for individualized, interactive experiences. We’re hiring for both full-time roles and 2026 internships — feel free to reach out!

Prior to Snap, I was a postdoctoral researcher at Stanford Computer Science and the Wu Tsai Human Performance Alliance, where I worked closely with Professors Serena Yeung, C. Karen Liu, and Scott Delp on 4D human reconstruction and generation. I completed my Ph.D. at the University of Toronto, advised by Professor Rich Zemel, with a focus on generative models and few-shot learning.


Selected Publications

See Google Scholar for an exhaustive list.

2025

  1. ICML
    "I Think, Therefore I Diffuse: Enabling Multimodal In-Context Reasoning in Diffusion Models" Zhenxing Mi, Kuan-Chieh Wang, Guocheng Qian, Hanrong Ye, Runtao Liu, Sergey Tulyakov, Kfir Aberman, and Dan Xu In ICML 2025
  2. CVPR
    "Omni-id: Holistic identity representation designed for generative tasks" Guocheng Qian, Kuan-Chieh Wang, Or Patashnik, Negin Heravi, Daniil Ostashev, Sergey Tulyakov, Daniel Cohen-Or, and Kfir Aberman In CVPR 2025

2024

  1. NeurIPS
    "Interpreting the weight space of customized diffusion models" Amil Dravid, Yossi Gandelsman, Kuan-Chieh Wang, Rameen Abdal, Gordon Wetzstein, Alexei Efros, and Kfir Aberman In NeurIPS 2024
  2. SIGA
    "MoA: Mixture-of-Attention for Subject-Context Disentanglement in Personalized Image Generation" Kuan-Chieh Wang, Daniil Ostashev, Yuwei Fang, Sergey Tulyakov, and Kfir Aberman In SIGGRAPH Asia 2024 📄 Paper 🌐 Project Page
  3. SIGGRAPH
    "Iterative Motion Editing with Natural Language" Purvi Goel, Kuan-Chieh Wang, C Karen Liu, and Kayvon Fatahalian In SIGGRAPH 2024 📄 Paper 🌐 Project Page
  4. ECCV
    "Viewpoint Textual Inversion: Unleashing Novel View Synthesis with Pretrained 2D Diffusion Models" James Burgess, Kuan-Chieh Wang, and Serena Yeung In ECCV 2024 📄 Paper 🌐 Project Page 🛠 Code

2023

  1. CVPR
    "PROB: Probabilistic Objectness for Open World Object Detection" Orr Zohar, Kuan-Chieh Wang, and Serena Yeung In CVPR 2023 📄 Paper 🛠 Code
  2. ICLR
    "DrML: Diagnosing and Rectifying Vision Models using Language" Yuhui Zhang, Jeff Z HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou, and Serena Yeung In ICLR 2023 📄 Paper 🛠 Code



Last updated: June 2025