Team

Samuel Albanie

Samuel is an Assistant Professor in the Department of Engineering at the University of Cambridge, a Fellow of the Alan Turing institute and a member of the ELLIS Society.

Andreea-Maria Oncescu

Andreea-Maria Oncescu is interested in computer vision, natural language applied to audio and video, unsupervised learning. She is based primarily in the Visual Geometry Group at the University of Oxford.

Co-supervised by Samuel Albanie and João F. Henriques.

Gyungin Shin

Gyungin Shin is interested in Computer Vision and Language. He is based primarily in the Visual Geometry Group at the University of Oxford. He is also a Research Scientist at AIFactory Korea

Co-supervised by Samuel Albanie and Weidi Xie.

Jonathan Roberts

Jonathan is interested in using computer vision and natural language to interpret satellite imagery. He is part of the Artificial Intelligence for Environmental Risks (AI4ER) CDT.

Co-supervised by Samuel Albanie and Kai Han.

Vishaal Udandarao

Vishaal Udandarao is interested in multi-modal representation learning (primarily vision-language modelling) in a lifelong learning setting. He is an ELLIS PhD student based primarily at the University of Tuebingen.

Co-supervised by Samuel Albanie and Matthias Bethge.

Tristan Dot

Tristan is interested in the links between computer vision representations and art historical theories. His research, in digital art history, is funded by a Gates Cambridge scholarship. He is part of the Cambridge Digital Humanities group.

Co-supervised by Samuel Albanie and Leo Impett.

Herbie Bradley

Herbie is a 2nd year PhD student in the AI for Environmental Risk CDT. Herbie's research interests are primarily related to large language models, including reinforcement learning from human feedback (RLHF), open-endedness with LLMs, interpretability, evaluations, AI governance, and more.

Mingkai Zheng

Mingkai Zheng is a Ph.D. student from The University of Sydney. His research interests lie in self-supervised learning, semi-supervised learning, and model pretraining. He is working on few-shot learning with foundation models for augmented scientists.

Alumni

• Liangchen Li (MS student, 2022 - 2023)
• Augustas Macijauskas (MS student, 2022 - 2023)
• Sowmen Das (MS student, 2022 - 2023)
• Tingrui He (undergraduate, 2022 - 2023)
• Mexi (Tracy) Chen (undergraduate, 2022 - 2023)
• Richard Zhang (undergraduate, 2022 - 2023)
• Anchit Jain (undergraduate, 2022 - 2023)
• Kaiqu Liang (MS student, 2021 - 2022, next steps: PhD student at Princeton)
• Shiyang Yu (undergraduate, 2021 - 2022, next steps: Meta)
• Dmitry Lubyako (undergraduate, 2021 - 2022, next steps: Da Vinci)
• Selina Xing (undergraduate, 2021 - 2022)