Hanshu YAN (严 汉书)   (Pronouns: he/him/his)          school Google Scholar     
    

Senior Research Scientist @ Salesforce AI Research

Ph.D in Machine Learning @ NUS

: hanshu.yan@outlook.com

His current work focuses on multimodal generation and understanding. He has led or co-led several relevant projects, including MagicEdit and MagicAvatar for video editing, PeRFlow for diffusion acceleration, and AdjointDPM for controllable generation. He was also involved in several large-scale multimodal projects, including Aria, MagicVideo, and Allegro. He will be dedicated to developing efficient and powerful models for video generation and understanding.

Hanshu did his PhD with Prof. Vincent Y. F. Tan and Dr. Jiashi Feng in NUS, with a research focus on robust deep vision models and optimizers. He also has been working closely with Dr. Junnan Li and Dr. Jun Hao Liew.

Academic Service: reviewer for ICML, ICLR, NeurIPS, CVPR, ACM Multimedia, etc.

Experiences

    Senior Research Scientist Rhymes.AI, Singapore 07/2024 - 12/2024
    Research Scientist ByteDance, Singapore 07/2022 - 07/2024

Education

    Ph.D,  Machine Learning NUS 2022
    M.Sc,  EE NUS 2017
    B.Eng, EE & Math BUAA 2015

Selected Papers

( * Equally contributed; ^AIGC, ^ML robustness, ^Learning algorithms, )

   ^ PeRFlow; Piecewise Rectified Flow as Universal Plug-and-Play Accelerator.
Hanshu Yan, Xingchao Liu, Jiachun Pan, Jun Hao Liew, Qiang Liu, Jiashi Feng
NeurIPS 2024  



   ^ DragDiffusion: Harnessing Diffusion Models for Interactive Point-based Image Editing.
Yujun Shi, Chuhui Xue, Jun Hao Liew, Jiachun Pan, Hanshu Yan, Wenqing Zhang, Vincent Y. F. Tan, Song Bai
CVPR 2024  


^ LightningDrag: Lightning Fast and Accurate Drag-based Image Editing Emerging from Videos.
Yujun Shi, Jun Hao Liew, Hanshu Yan, Vincent Y. F. Tan, Jiashi Feng
arXiv 2024


   ^ MagicVideo-V2: Multi-Stage High-Aesthetic Video Generation.
Weimin Wang, Jiawei Liu, Zhijie Lin, Jiangqiao Yan, Shuo Chen, Chetwin Low, Tuyen Hoang, Jie Wu, Jun Hao Liew, Hanshu Yan, Daquan Zhou, Jiashi Feng
arXiv 2024  
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^ MagicVideo: Efficient Video Generation With Latent Diffusion Models.
Daquan Zhou, Weimin Wang, Hanshu Yan, Weiwei Lv, Yizhe Zhu, Jiashi Feng
arXiv 2023  


   ^ MagicEdit: High-Fidelity and Temporally Coherent Video Editing.
Jun Hao Liew*, Hanshu Yan*, Jianfeng Zhang, Zhongcong Xu, Jiashi Feng
arXiv 2023  


^ MagicAvatar: Multimodal Avatar Generation and Animation.
Jianfeng Zhang*, Hanshu Yan*, Zhongcong Xu*, Jiashi Feng, Jun Hao Liew*
arXiv 2023  
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^ MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model.
Zhongcong Xu, Jianfeng Zhang, Jun Hao Liew, Hanshu Yan, Jia-Wei Liu, Chenxu Zhang, Jiashi Feng, Mike Zheng Shou
CVPR 2024  



   ^ MagicProp: Diffusion-based Video Editing via Motion-aware Appearance Propagation.
Hanshu Yan*, Jun Hao Liew*, Long Mai, Shanchuan Lin, Jiashi Feng
arXiv 2023


   ^ AdjointDPM: Adjoint Sensitivity Method for Gradient Backpropagation of Diffusion Probabilistic Models.
Jiachun Pan*, Jun Hao Liew, Vincent Y. F. Tan, Jiashi Feng, Hanshu Yan*
ICLR 2024  
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^ SAG: Towards Accurate Guided Diffusion Sampling through Symplectic Adjoint Method.
Jiachun Pan*, Hanshu Yan*, Jun Hao Liew, Jiashi Feng, Vincent Y. F. Tan
arXiv 2023


   ^ MagicMix: Semantic Mixing with Diffusion Models.
Jun Hao Liew*, Hanshu Yan*, Daquan Zhou, Jiashi Feng
arXiv 2022


   ^ Towards Adversarially Robust Deep Image Denoising.
Hanshu Yan, Jingfeng Zhang, Jiashi Feng, Masashi Sugiyama, Vincent Y. F. Tan
IJCAI 2022
   ^ CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection.
Hanshu Yan, Jingfeng Zhang, Gang Niu, Jiashi Feng, Vincent Y. F. Tan, Masashi Sugiyama
ICML 2021
   ^ On Robustness of Neural Ordinary Differential Equations.
Hanshu Yan, Jiawei Du, Vincent Y. F. Tan, Jiashi Feng
ICLR 2020 Spotlight


   ^ Efficient Sharpness-aware Minimization for Improved Training of Neural Networks .
Jiawei Du, Hanshu Yan, Jiashi Feng, Joey Tianyi Zhou, Liangli Zhen, Rick Siow Mong Goh, Vincent Y. F. Tan
ICLR 2022
   ^ Towards Understanding Why Lookahead Generalizes Better Than SGD and Beyond.
Pan Zhou, Hanshu Yan, Xiaotong Yuan, Jiashi Feng, Shuicheng Yan
NeurIPS 2021