Cheng Wan

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Hi there! I’m an ECE Ph.D. student at Cornell University, and I’m honored to be advised by Mert Sabuncu and Qingyu Zhao. In Summer 2026, I was a research intern on the Adobe Firefly foundation model team, working on large-scale pre-training and post-training of generative models. Previously, I worked on computer vision at CMU and on AI for healthcare at Georgia Tech and Emory.

Research Interests: Generative modeling (diffusion / flow matching, image & video generation), multimodal reasoning, and foundation-model pre-/post-training (on-policy distillation, RL), with applications to medical imaging.

Experience

Adobe – Firefly Foundational Models Team May 2026 – Aug 2026
Research Intern
Large-scale pre-training of generative foundation models; post-training with on-policy distillation (OPD) and RL.

Publications

  1. Cheng Wan, Chenjun Li, and Qingyu Zhao
    Under review, 2026
  2. Cheng Wan, Yusu Qian, and Qingyu Zhao
    NeurIPS 2026
  3. Cheng Wan, Bahram Jafrasteh, Ehsan Adeli, Miaomiao Zhang, and Qingyu Zhao
    IEEE Trans. on Medical Imaging (TMI)
  4. Cheng Wan*, Hongyuan Yu*, Zhiqi Li*, Yihang Chen, Yajun Zou, Yuqing Liu, Xuanwu Yin, and Kunlong Zuo
    Oral & Winner Award @ NTIRE Workshop - CVPR 2024
  5. FlowMap-OPD: Rollout–Kernel Separation for On-Policy Distillation of Few-Step Flow-Map Generators
    Zhiqi Li, Cheng Wan, and Bo Zhu
    Under review, 2026
  6. LongCoref-AV: Benchmarking Audio-Visual Identity Coreference in Long-Form Video
    Zhexiao Xiong, Huijuan Huang, Philip Anastassiou, Cheng Wan, Jing Shi, Manuel Brack, Yuheng Li, Ajinkya Kale, and Nathan Jacobs
    Under review, 2026

Academic Service

Reviewer: NeurIPS (2024–2026), ICLR (2025–2026), ICML (2025), AISTATS (2025–2026)
Workshop Reviewer: NeurIPS AI4Science (2025–2026), NeurIPS SPIGM (2025–2026), ICML AI4Science (2024)

Teaching

  • Teaching Assistant (Co-lecturer), ECE 5200/3200: Foundations of Machine Learning, Cornell University Spring 2025