Spontaneous neuronal activation · 2026–present

Lois group, Caltech

Computational modelling of spontaneous neuronal activity and its role in the restoration of learned behaviours following perturbation. Drawing on attractor network theory and Hebbian plasticity. Also worked on preprocessing of fMRI data (ongoing project). Part of the Cambridge–Caltech exchange, funded by Caltech and St Catharine's College, Cambridge.

Viral ancestral recombination graphs · 2025–present

Department of Genetics, University of Cambridge

Scalable inference of ancestral recombination graphs for viral DNA, using Markov Chain Monte Carlo and perturbation theory. Awarded the J.M. Thoday Prize for the best undergraduate research project.

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Deep learning for genome organisation · 2025–present

Hannon Group, Cancer Research UK Cambridge Institute

Deep learning for predicting three-dimensional chromatin organisation from sequencing data, in the laboratory of Greg Hannon. Work focused on learning sequence determinants of topologically associating domains and compartment structure. Publication in preparation.

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Lock-in risk benchmark for LLM systems · 2025

Supervised Program for Alignment Research

Paper under review.

Structural biology of transcription · 2024

Department Cramer, Max Planck Institute for Multidisciplinary Sciences, Göttingen

Studied +1 nucleosome promoter-proximal pausing in eukaryotic transcription. Independently designed biochemical assays, and developed skills in cryo-electron microscopy. Funded by the Max Planck Institute for Multidisciplinary Sciences.

Hidden Markov Models for fast protein kinetics · 2023

Haran Group, Weizmann Institute of Science

Inference of conformational state sequences from single-molecule FRET data using hidden Markov models. Work addressed the challenge of fast dynamics on timescales shorter than photon-arrival intervals. Funded by the Weizmann UK Foundation.

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