Saining Xie

Saining Xie is an Assistant Professor of Computer Science at NYU Courant Institute of Mathematical Sciences and affiliated with the NYU Center for Data Science. He leads the CILVR research group and teaches courses including Computer Vision, Machine Learning, and Learning with Large Language and Vision Models at the graduate level.

His educational background includes a Ph.D. and M.S. from UC San Diego's CSE Department under Zhuowen Tu's supervision, and a bachelor's degree from Shanghai Jiao Tong University. During his doctoral studies, he interned at NEC Labs, Adobe, Facebook, Google, and DeepMind.

Dr. Xie's research focuses on advancing robust visual intelligence through scalable and reliable systems that interpret visual events and develop common sense understanding of the world. His work spans computer vision, machine learning, representation learning, and multimodal systems, with particular emphasis on developing architectures that bridge vision and language understanding.

His publications demonstrate significant contributions to vision-language models, diffusion models, convolutional neural networks, and 3D scene understanding, with numerous papers appearing at top conferences including NeurIPS, CVPR, and ICCV, often receiving recognition as oral or spotlight presentations.

• Oral Presentation at NeurIPS 2024
• Oral Presentation at CVPR 2024
• Spotlight Presentation at ICLR 2023
• Oral Presentation at ICCV 2023
• Best Paper Nomination at CVPR 2020

Dr. Xie actively mentors PhD students including Ellis Brown, Fred Lu, Xichen Pan, Peter Tong, and others. He has organized major tutorials at CVPR and ECCV on Visual Recognition for Images, Video, and 3D, and his research has practical applications in visual grounding, multimodal reasoning, and robust AI systems. His lab maintains strong connections with industry research labs including FAIR, where he previously worked as a research scientist.