Christina Lu

Christina Lu

Doctoral Student

Student, Kellogg College

E: christina.lu@cs.ox.ac.uk

Themes:

• Human Centered Computing

Interests

evolutionary algorithms, AI-AI communication, online learning, multi-modal models, ecological models, embodied cognition, philosophy of computation

Biography

Christina Lu is an AI researcher and technologist based in London, via Cupertino and Shanghai. Her work combines rigorous technical research with speculative philosophical analysis and illustrative world-building to instantiate a more viable future with artificial intelligence. She is a doctoral student in computer science at Oxford, prototyping techniques for machine learning models inspired by the generative frictions of evolution. She is also an affiliate researcher at Antikythera, a thinktank for the philosophy of computation, hosted by the Berggruen Institute—where she was a researcher in the inaugural 2023 studio.

Previously, she was a software engineer at DeepMind, building systems for ML experimentation at scale and publishing sociotechnical research. Her work on the Whole Earth Codec, a proposal for a multi-modal foundation model trained on planetary-scale ecological sensing, and Vivarium, a vaporware platform for training AI in embodied cognition through modular "toy world" simulations, has been supported by Antikythera, Serpentine Arts Technologies, RadicalxChange, and PACT Zollverein. She is a frequent co-conspirator at Trust, where she mentors projects for Trust Quests.

She has given talks at Google People + AI Research (PAIR), Central Saint Martins, and Design Academy Eindhoven, and appeared on podcasts such as The Good Robot and Medialab Matadero's Synthetic Minds. Christina's research at Oxford is funded by the Scholarship for Women in Computer Science from the department and the James B. Reynolds Scholarship for Foreign Study from Dartmouth. She has a BA in Computer Science and Studio Art from Dartmouth.

Selected Publications

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• The subtle language of exclusion

  Christina Lu and David Jurgens

  In Proceedings of the Sixth Workshop on Online Abuse and Harms (WOAH). Pages 79–91. Association for Computational Linguistics. July, 2022.

  Details about The subtle language of exclusion | BibTeX data for The subtle language of exclusion | DOI (10.18653/v1/2022.woah-1.8) | Link to The subtle language of exclusion

• Subverting machines‚ fluctuating identities: Re−learning human categorization

  Christina Lu‚ Jackie Kay and Kevin McKee

  In Proceedings of the 2022 ACM Conference on Fairness‚ Accountability‚ and Transparency. Pages 1005–1015. Association for Computing Machinery. 2022.

  Details about Subverting machines‚ fluctuating identities: Re−learning human categorization | BibTeX data for Subverting machines‚ fluctuating identities: Re−learning human categorization | DOI (10.1145/3531146.3533161) | Link to Subverting machines‚ fluctuating identities: Re−learning human categorization

Supervisor