Ze Liu (刘泽)

Ze Liu is currently a Member of Technical Staff at xAI , where he is dedicated to advancing the development of Artificial General Intelligence (AGI). His research primarily revolves around buliding large multi-modal models and making knowledge for large language models.

He received his Ph.D. degree from the University of Science and Technology of China (USTC) and Microsoft Research Asia (MSRA) in 2024, specializing in designing visual architectures and developing large-scale vision/multi-modal models, under the supervision of Prof. Baining Guo and Prof. Yong Wang. During his Ph.D. studies, he collaborated closely with Han Hu, Yue Cao and Zheng Zhang, as a research intern at Microsoft Research Asia (MSRA) from 2019 to 2024. Prior to that, he received his B.S. degree from USTC in 2019 with the highest honor, the "Guo Moruo Scholarship".

His work of Swin Transformer won the Best Paper Award (Marr Prize) of ICCV 2021. Additionally, he was selected as a recipient of the Microsoft Research PhD Fellowship in 2022.

Email / Google Scholar / Github / X / LinkedIn

Recent News

[2023/03] Our work of Tutel-MoE was accepted by MLSys 2023.
[2023/03] One paper accepted by CVPR 2023.
[2022/11] One spotlight paper accepted by NeurIPS 2022.
[2022/03] Two papers accepted by CVPR 2022.
[2021/10] Our Swin Transformer won the Best Paper Award (Marr Prize) of ICCV 2021!
[2021/07] Two papers with one oral accepted by ICCV 2021.
[2021/06] Our Video Swin Transformer achieves new SOTA on Kinetics-400 , Kinetics-600 and Something-Something V2 .
[2021/04] Code available for Group-Free 3D Object Detection via Transformers
[2021/04] Code and pretrained models for Swin Transformer (object detection , semantic segmentation) are released.
[2021/03] Our Swin Transformer achieves new SOTA on COCO detection and ADE20K semantic segmentation .
[2020/07] One paper accepted by ECCV 2020.

Selected Publications
(* indicates equal contribution)

	Could Giant Pretrained Image Models Extract Universal Representations? Yutong Lin, Ze Liu, Zheng Zhang, Han Hu, Nanning Zheng, Stephen Lin, Yue Cao Neural Information Processing Systems (NeurIPS), 2022 Spotlight paper
	Swin Transformer V2: Scaling Up Capacity and Resolution Ze Liu, Han Hu, Yutong Lin, Zhuliang Yao, Zhenda Xie, Yixuan Wei, Jia Ning, Yue Cao, Zheng Zhang, Li Dong, Furu Wei, Baining Guo IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022 CVPR 2022 Top-10 Influential Papers (Rank 9) paper / code Star
	Video Swin Transformer Ze Liu, Jia Ning, Yue Cao, Yixuan Wei, Zheng Zhang, Stephen Lin, Han Hu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022 CVPR 2022 Top-10 Influential Papers (Rank 4) paper / code Star
	Swin Transformer: Hierarchical Vision Transformer using Shifted Windows Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, Baining Guo International Conference on Computer Vision(ICCV), 2021 Best Paper Award (Marr Prize)! paper / code Star
	Group-Free 3D Object Detection via Transformers Ze Liu, Zheng Zhang, Yue Cao, Han Hu, Xin Tong International Conference on Computer Vision(ICCV), 2021 paper / code Star
	A Closer Look at Local Aggregation Operators in Point Cloud Analysis Ze Liu, Han Hu, Yue Cao, Zheng Zhang, Xin Tong European Conference on Computer Vision(ECCV), 2020 paper / code Star

Selected Honors

Frontiers of Science Awards.
2023
Microsoft Research PhD Fellowship.
2022
ICCV Best Paper Award (Marr Prize).
2021
World Artificial Intelligence Conference Youth Outstanding Paper Award.
2021
Guo Moruo Scholarship (The highest honor in USTC , 33 graduates per year).
2019
National Scholarship.
2021, 2017
Outstanding graduates of USTC.
2019
Chinese Academy of Sciences Scholarship.
2017
First Prize, National Undergraduate Electronics Design Contest.
2017

Professional Services

Journal Reviewer: TPAMI, TIP, NEUCOM, PR, TNNLS.
Conference Reviewer: CVPR, ICCV, ECCV, NeurIPS.

Modified from Jon Barron