Welcome to my website! Currently, I am a PhD student with Máté Lengyel in the Computational and Biological Learning group at the University of Cambridge, developing and applying state-of-the-art methods for neural data analysis with a focus on studying neural variability. I have also worked at Meta Reality Labs CTRL as a research scientist intern building EMG neuromotor interfaces, and at G-research London as a quantitative research intern working on deep learning for timeseries prediction. Before this, I completed the Natural Sciences Tripos specializing in computational and theoretical physics, with my thesis on synchronization in simplified models of cilia supervised by Pietro Cicuta.

My main interests lie in neuroscience, machine learning and their intersection. In particular, I am excited about building a more mechanistic understanding of artificial neural networks, characterizing spiking variability in neural spike train recordings, and studying computations in spiking neural networks beyond analog rate models. I also retain an active interest in physics, in particular in its interfaces with biology and machine learning. In addition, I have a keen interest in cell biology, with strong exposure to the subject prior to focussing on physics.

See my CV for more details.