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Guocheng Qian

钱国成

Research Scientist at Snap Research

Snap Research

Gordon Guocheng Qian

Welcome! I am a research scientist at Snap Research working on Personalized Generative AI. I earned my Ph.D. in Computer Science from KAUST, where I was fortunate to be advised by Prof. Bernard Ghanem. Prior to that, I received my B.Eng degree from Xi'an Jiaotong University (XJTU), China with the university’s highest undergraduate honor. My primary research interests lie in computer vision and generative models. My representative work includes PointNeXt (NeurIPS), Magic123 (ICLR) and Omni-ID (CVPR'25).
If you are interested in working in generative models with us, please drop me a message through guocheng.qian [at] outlook.com

Education

Interests

Experience

 
 
 
 
 

Research Scientist

Dec 2023 – Present Palo Alto, USA
Work with Kfir Aberman on personalized AI generation. Projects: Omni-ID (CVPR'25), ComposeMe (preprint)
 
 
 
 
 

Research Scientist Intern

May 2023 – Sep 2023 Santa Monica, CA, USA
Projects: high-quality 3D generation Magic123 (ICLR'24), AToM (preprint)
 
 
 
 
 

AI Research Scientist Intern

Aug 2022 – Jan 2023 San Jose, CA, USA
Project: efficient long video understanding
 
 
 
 
 

Remote Job

Dec 2021 – May 2022 remote
Worked with Houwen Peng on point cloud processing backbone, data scaling and training PointNeXt (NeurIPS'22).
 
 
 
 
 

Research Intern

Jun 2020 – Dec 2021 Remote
Worked with Xiangyu Zhang and Xuanyang Zhang on atuomated architecture search project TNAS (CVPRW'22).
 
 
 
 
 

Computer Vision Research Intern

Jul 2018 – May 2019 Shenzhen, China
Worked with Jimmy S. Ren and Dong Chao on paper end-to-end raw image quality enhancement ISPNet (ICCP'22).

Accomplish­ments

CEMSE Dean’s List Award (year 21/22)

Awarded to Top 20%.

CEMSE Research Excellence Award (year 21/22)

Awarded to less than a handful of students, following nominations and based on research achievement.

KAUST Fellowship for MS and PhD Studies

Fellowship covering ​full tuition support, monthly living allowance, housing, and medical coverage.

Outstanding Undergraduate

Highest undergraduate honor awarded to 10 selected undergraduates

National First Class Scholarship

Highest scholarship awarded to TOP 2% unversity student.

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