CV

General Information

Full Name Chaoran Cheng
Affiliation Siebel School of Computing and Data Science, University of Illinois Urbana-Champaign
Email chaoran7 [at] illinois.edu
Website ccr-cheng.github.io

Education

  • 2022 - 2027
    Ph.D. candidate in Computer Science
    Siebel School of Computing and Data Science, University of Illinois Urbana-Champaign
  • 2018 - 2021
    B.S. in Computer Science
    School of Electronics Engineering and Computer Science, Peking University
  • 2017 - 2018
    Chemistry and Molecular Engineering
    College of Chemistry and Molecular Engineering, Peking University
    • Transferred to the School of Electronics Engineering and Computer Science

Work Experience

  • 2026
    NVIDIA
    Research Scientist Intern, Fundamental Generative AI Research; San Jose, CA
    • May 2026 - Nov. 2026 (expected)
  • 2025 - 2026
    ByteDance Seed
    Research Scientist Intern, Protenix team; Seattle, WA
    • May 2025 - Jan. 2026
  • 2024
    Amazon AWS AI
    Applied Scientist Intern under Dr. Bernie Wang; San Jose, CA
    • May 2024 - Aug. 2024
  • 2023 - 2024
    Microsoft Research AI4Science
    Research Intern under Dr. Tong Wang; Beijing, China
    • May 2023 - Jan. 2024
    • Contributed to AI2BMD (Nature, 2024) for large-scale protein molecular dynamics simulation with ab initio accuracy
  • 2021 - 2022
    Helixon (now Earendil Labs)
    Research Scientist under Dr. Jian Peng; Beijing, China
    • Aug. 2021 - July 2022

Award

  • 2026
    Ross J. Martin Award
    The Grainger College of Engineering, University of Illinois Urbana-Champaign
    • For outstanding research achievement; the sole college-wide graduate student recipient

Selected Publications

  • Fully Atomic Protein Co-Design with Unified Multimodal Diffusion
    Chaoran Cheng*, Jiaqi Guan*, Milong Ren, Chengyue Gong, Cong Liu, Xinshi Chen, Ge Liu, Wenzhi Xiao. Preprint, 2026.
  • Variable-Length Generative Protein Design via Generalized Poisson Flow
    Chaoran Cheng*, Zhanghan Ni*, Yanru Qu*, Yuxin Chen, Ruihan Guo, Jiajun Fan, Ge Liu. Preprint, 2026.
  • Accurate de novo Design of Peptides from Programming Biophysical Landscape
    Mingyu Li, Yini Liu, Jie Zhong, Xinchao Shi, Jiqing Zheng, Kai Wang, Yunxia Cui, Chaoran Cheng, Shijin Li, Xiangzhe Kong, Shaoning Li, Miaojie Xv, Chunhao Zhu, Xiaobing Lan, He Yang, Kewei Chang, Zhenyu An, Shizhang Wan, Xiuyan Yang, Qiancheng Shen, H. Eric Xu, Zihua Wang, Lei Liu, Youwen Zhuang, Jianzhu Ma, Jian Zhang. Under review at Science, 2026.
  • MutAtlas: A PDB-Wide Energy-Guided Atlas of Protein Mutation Effects
    Ruihan Guo*, Chaoran Cheng*, Zhanghan Ni, Neil He, Bangji Yang, Ge Liu. ICML 2026.
  • Riemannian Consistency Model
    Chaoran Cheng*, Yusong Wang*, Yuxin Chen, Xiangxin Zhou, Nanning Zheng, Ge Liu. NeurIPS 2025.
  • Gradient-Free Generation for Hard-Constrained Systems
    Chaoran Cheng, Boran Han, Danielle C. Maddix, Abdul Fatir Ansari, Andrew Stuart, Michael W. Mahoney, Bernie Wang. ICLR 2025.
  • Training-Free Guided Flow-Matching with Optimal Control
    Luran Wang, Chaoran Cheng, Yizhen Liao, Yanru Qu, Ge Liu. ICLR 2025.
  • Ab initio Characterization of Protein Molecular Dynamics with AI2BMD
    Tong Wang, Xinheng He, Mingyu Li, Yatao Li, Yusong Wang, Ran Bi, Chaoran Cheng, Xiangzhen Shen, Jiawei Meng, He Zhang, Bin Shao, Haiguang Liu, Zun Wang, Shaoning Li, Tie-Yan Liu. Nature, 2024.
  • Categorical Flow Matching on Statistical Manifolds
    Chaoran Cheng, Jiahan Li, Jian Peng, Ge Liu. NeurIPS 2024.
  • Neural P3M: A Long-Range Interaction Modeling Enhancer for Geometric GNNs
    Yusong Wang*, Chaoran Cheng*, Shaoning Li*, Yuxuan Ren, Bin Shao, Ge Liu, Pheng-Ann Heng, Nanning Zheng. NeurIPS 2024.
  • Full-Atom Peptide Design Based on Multi-Modal Flow Matching
    Jiahan Li, Chaoran Cheng, Zuofan Wu, Ruihan Guo, Shitong Luo, Zhizhou Ren, Jian Peng, Jianzhu Ma. ICML 2024.
  • Equivariant Neural Operator Learning with Graphon Convolution
    Chaoran Cheng, Jian Peng. NeurIPS 2023 (Spotlight).

Teaching & Other Research Activity

  • Teaching Assistant for UIUC CS444 Deep Learning for Computer Vision (Fall 2023)
  • Workflow Chair for the New Frontiers in Graph Learning Workshop (NeurIPS 2023)
  • Program Chair & Organizer for the UIUC BCB Mini Conference (2026)

Additional Information

Languages Mandarin (native); German (novice)
Computer Skills Python and PyTorch (proficient); C and C++ (versed); JavaScript, CSS, and HTML (familiar)
Interests Art and music; passed Tenth Grade (the highest amateur grade) in piano