I completed my PhD at University of Edinburgh supervised by Dr. Matthias Hennig. I am now a postdoctoral researcher at the Zuckerman Institute at Columbia University, working with Dr. Liam Paninski. I am a member of the International Brain Laboratory (IBL) and the NSF AI Institute for Artificial and Natural Intelligence (ARNI).

My research lies at the intersection of machine learning and systems neuroscience, with a focus on developing neuro-foundation models: large-scale, pretrained models of brain activity that generalize across animals, brain regions, and tasks. I also co-created SpikeInterface, a widely-used open-source framework for creating flexible and robust spike sorting pipelines.

Recent News

• I co-organized the workshop Building a foundation model for the brain at Cosyne 2025 in Mont Tremblant, Canada.
• Our work Neural Encoding and Decoding at Scale was accepted at ICML 2025 as a spotlight.
• Our work In vivo cell-type and brain region classification via multimodal contrastive learning was accepted at ICLR 2025 as a spotlight.
• Our work Towards a “universal translator” for neural dynamics at single-cell, single-spike resolution was accepted at NeurIPS 2024.
• Our work Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling and cloud-native open-source tools was published in Nature Methods.
• Our work Towards robust and generalizable representations of extracellular data using contrastive learning was accepted at NeurIPS 2023.
• Our work Bypassing spike sorting: Density-based decoding using spike localization from dense multielectrode probes was accepted at NeurIPS 2023 as a spotlight paper.