I’m a postdoc at Stanford University where I work with Krishna Shenoy and Scott Linderman. I’m interested in neural population dynamics, latent variable models and stochastic processes, as well as probabilistic unsupervised machine learning methods in general. Broadly, I use data analysis and theoretical modelling approaches to study neural computation through the lens of dynamical systems.

I did my PhD work at the Gatsby Computational Neuroscience Unit at University College London under the supervision of Maneesh Sahani. I have an undergraduate degree in Natural Sciences and a master’s degree in Computational Statistics and Machine Learning, both from UCL. Before starting my PhD, I was a research assistant in Jonathan Pillow’s group at the Princeton Neuroscience Institute, where I developed scalable methods for Bayesian receptive field inference.