Yutong (Kelly) He 何雨桐

Contact: yutonghe [at] cs [dot] cmu [dot] edu

kelly2024.JPG

PhD Student @ MLD, SCS, CMU

yutonghe [at] cs [dot] cmu [dot] edu

I am a fourth-year PhD student in the Machine Learning Department, School of Computer Science at Carnegie Mellon University, advised by Prof. Zico Kolter and Prof. Ruslan Salakhutdinov.

Before coming to CMU, I was a master’s student at Stanford Computer Science with distinction in research. I was advised by Prof. Stefano Ermon, and closely worked with Prof. Christopher Manning, Prof. David Lobell and Prof. Marshall Burke. I completed my B.S in Mathematics and B.S. in Data Science with highest distinction at University of Rochester, where I worked with Prof. Henry Kautz and Prof. Jiebo Luo.

I am a Qualcomm Innovation Fellowship winner and was selected as a Siebel Scholar and a Xerox Engineering Research Fellow. I was also awarded an Outstanding Paper Award at ICLR 2022 and Doris Ermine Smith Award for Achievement in Mathematics.

My research focuses on generative modeling and machine learning.

Selected Papers

  1. ICLR
    Joint Distillation for Fast Likelihood Evaluation and Sampling in Flow-based Models
    Xinyue Ai*, Yutong He*, Albert Gu, Ruslan Salakhutdinov, J Zico Kolter, Nicholas Matthew Boffi, and Max Simchowitz
    In International Conference on Learning Representations (ICLR) 2026
    Paper Code Website
  2. TMLR
    Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation
    Yutong He, Alexander Robey, Naoki Murata, Yiding Jiang, Joshua Nathaniel Williams, George J. Pappas, Hamed Hassani, Yuki Mitsufuji, Ruslan Salakhutdinov, and J Zico Kolter
    Transactions on Machine Learning Research (TMLR) 2025
    Paper Code Website
  3. NeurIPS Workshop
    Blind Inverse Problem Solving Made Easy by Text-to-Image Latent Diffusion
    Michail Dontas*, Yutong He*, Naoki Murata, Yuki Mitsufuji, J Zico Kolter, and Ruslan Salakhutdinov
    In SPIGM @ NeurIPS 2025
    Paper Website
  4. ICLR
    Manifold Preserving Guided Diffusion
    Yutong He*, Naoki Murata*, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Dongjun Kim, Wei-Hsiang Liao, Yuki Mitsufuji, J. Zico Kolter, Ruslan Salakhutdinov, and Stefano Ermon
    In International Conference on Learning Representations (ICLR) 2024
    Paper Code Website
  5. arXiv
    Localized Text-to-Image Generation for Free via Cross Attention Control
    Yutong He, Ruslan Salakhutdinov, and J. Zico Kolter
    arXiv preprint 2023
    Paper Website
  6. ICLR Oral Award
    Comparing Distributions by Measuring Differences that Affect Decision Making
    Shengjia Zhao*, Abhishek Sinha*, Yutong He*, Aidan Perreault, Jiaming Song, and Stefano Ermon
    In International Conference on Learning Representations (ICLR) 2022
    Outstanding Paper Award [Top 0.15%]
    Oral Presentation [Top 1.6%]
    Paper Code Video
  7. ICLR
    SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations
    Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon
    In International Conference on Learning Representations (ICLR) 2022
    Paper Code Website