Sheng Li

Ph.D. Student at the University of Pittsburgh

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Hi! I am Sheng Li. I am currently a Ph.D. student in Department of Computer Science at the University of Pittsburgh, advised by Dr. Xulong Tang. I received my B.E. degree in Software Engineering from Sichuan University, China, in 2020.

My research focuses on designing and optimizing Efficient Machine Learning Algorithms and Systems, spanning applications in Diffusion-based Video Generation, RAG-enabled LLM Serving, Self-supervised Contrastive Learning, Supervised Model Training, and 3D Gaussian Splatting. My research targets platforms ranging from large-scale cloud clusters to resource-constrained edge devices.

✨ I am currently seeking both full-time and internship opportunities in positions including, but not limited to, Research Scientist, Applied Scientist, Research Engineer, Machine Learning Engineer, and Software Development Engineer. Please feel free to contact me if you have any suitable opportunities.

News

02/2026 One first-author paper on Efficient Video Diffusion is submitted to ECCV2026!
02/2026 One paper is accepted to CVPR 2026. This is the intern project in Adobe! Thanks to all collaborators!
05/2025 Joining Adobe Research as a Research Scientist/Engineer Intern!
01/2025 One paper is accepted to ICLR 2025. Thanks to all collaborators!
09/2024 One paper is accepted to ASP-DAC 2025. Thanks to all collaborators!

Experiences

Adobe, May 2025 – November 2025
Research Scientist/Engineer Intern
Mentor: Dr. Yifan Gong
Topic: Efficient Diffusion-based Video Generation

Selected Publications

  1. CVPR
    Content-Aware Dynamic Patchification for Efficient Video Diffusion
    Sheng Li, Connelly Barnes, Mamshad Nayeem Rizve, Hongwu Peng, Zhengang Li, Ohi Dibua, Alireza Ganjdanesh, Xulong Tang, Yan Kang, and Yifan Gong
    In The IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2026
  2. ICLR
    Mutual Effort for Efficiency: A Similarity-based Token Pruning for Vision Transformers in Self-Supervised Learning
    Sheng Li*, Qitao Tan*, Yue Dai, Zhenglun Kong, Tianyu Wang, Jun Liu, Ao Li, Ninghao Liu, Yufei Ding, Xulong Tang, and Geng Yuan
    In The Thirteenth International Conference on Learning Representations, 2025
  3. ICLR
    Waxing-and-Waning: a Generic Similarity-based Framework for Efficient Self-Supervised Learning
    Sheng Li, Chao Wu, Ao Li, Yanzhi Wang, Xulong Tang, and Geng Yuan
    In The Twelfth International Conference on Learning Representations, 2024
  4. ICLR
    SmartFRZ: An Efficient Training Framework using Attention-Based Layer Freezing
    Sheng Li*, Geng Yuan*, Yue Dai*, Youtao Zhang, Yanzhi Wang, and Xulong Tang
    In The Eleventh International Conference on Learning Representations, 2023
  5. NeurIPS
    Layer freezing & data sieving: missing pieces of a generic framework for sparse training
    Geng Yuan*, Yanyu Li*Sheng Li, Zhenglun Kong, Sergey Tulyakov, Xulong Tang, Yanzhi Wang, and Jian Ren
    Advances in Neural Information Processing Systems, 2022