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Assistant Professor

University of Cambridge

Email: sw2181 AT cam.ac.uk

Office: BE454, Baker Building


Elliott / Shangzhe Wu

I am an Assistant Professor in the Department of Engineering at the University of Cambridge. Our research team develops computer vision and AI techniques for dynamic physical world modeling, with applications across simulation, robotics, and physical AI in general.

Previously, I was a postdoc at Stanford University, working with Jiajun Wu. I completed my PhD in the Visual Geometry Group (VGG) at the University of Oxford, advised by Andrea Vedaldi and Christian Rupprecht, and my BSc in Computer Science from HKUST, where I worked with Chi-Keung Tang and Yu-Wing Tai.



Highlights:

[12/2026]: We are organizing the Workshop on Physical World AI at NeurIPS 2026 in Atlanta, US.

[03/2026]: I'm looking for a PhD student with UK home fee status to join our team. If you're interested and have research experience in multimodal spatial modeling or vision-based robot learning, send me an email with your CV and confirm your eligibility for UK home fee status.

[10/2024]: Humbled to receive the ECVA PhD Award!

[11/2023]: Honored to receive the BMVA Sullivan Doctoral Thesis Prize!

[06/2020]: Our work on Unsupervised 3D received the Best Paper Award at CVPR 2020!


Teaching:


Recent Talks:

[2026/03] From Pixels to Motion

[2024/05] Physical Natural World from Images


Research Team



Lu Chen

Lu Chen

Visiting PhD, Zhejiang University
2026-

Fernando Cendra

Fernando Cendra

Pre-Doc, École des Ponts ParisTech
2026-
(with Gül Varol)

Agniv Sharma

Agniv Sharma

PhD, UTN
2026-
(with Yuki Asano)

Shenhan Qian

Shenhan Qian

ELLIS PhD, TUM
2025-
(with Daniel Cremers)

Yuxin Yao

Yuxin Yao

PhD, Cambridge
2025-
(with Joan Lasenby)

Chexuan Qiao

Chexuan Qiao

PhD, Cambridge
2025-
(with Roberto Cipolla)

Past Members

Xiaoyang Lyu

Xiaoyang Lyu

Visiting PhD, HKU
2025-2026

Ray / Ruining Li

Ray / Ruining Li

Visiting PhD, Oxford
2025-2026

Matt Zhou

Matt Zhou

Visiting Researcher
2025-2026


Publications


( * and indicate equal contribution or alphabetical order )