Lucy Farnik
Bio
Updated 03/22/26Lucy Farnik is a PhD student at the University of Bristol (2023 cohort) in the UKRI Centre for Doctoral Training in Interactive Artificial Intelligence, supervised by Dr Conor Houghton and Mengyue Yang, with her research titled "Towards interpretable and controllable deep language modeling." She completed ARENA and the MATS research program under the mentorship of Neel Nanda at Google DeepMind, during which she explored SAE-based circuit-style analysis — work that led to an LTFF extension grant. Her research focuses on mechanistic interpretability of large language models, particularly sparse autoencoders (SAEs), with publications including "Residual Stream Analysis with Multi-Layer SAEs" (ICLR 2025) and "Jacobian Sparse Autoencoders: Sparsify Computations, Not Just Activations" (ICML 2025). She has also been affiliated with FAR.AI and co-founded BAISC (Bristol AI Safety Student Community), a student research centre focused on AI safety. Her background includes a BEng in Computer Science with Innovation from the University of Bristol and extensive software engineering experience starting from an early age.
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Links
Updated 03/22/26- Personal Website
- https://lucyfarnik.github.io/
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- LessWrong
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