I am a PhD student and Cambridge Gates scholar working with Guillaume Hennequin in the Computational and Biological Learning Lab at the University of Cambridge. We have recently worked on a suite of Bayesian machine learning tools for analysing neural population recordings which we apply to diverse circuits involved in navigation, cognition, motor control etc. in order to better understand how neural circuit dynamics give rise to biological function. We are also working on new approaches for continual learning inspired by principles of Bayesian inference, and in parallel I work with the Ölveczky lab at Harvard Center for Brain Science to investigate the mechanistic underpinnings of continual learning and the persistence of memories in biological motor circuits. In addition to our neuroscience research, CBL is home to a range of excellent Machine Learning researchers, and we are always interested in thinking about new ways of applying neuroscience to machine learning and vice versa.

Prior to my PhD, I worked with the Ölveczky lab as part of my MPhil in Computational Biology, and with Vivek Jayaraman at Janelia Research Campus as a Janelia Undergraduate Scholar (see projects and publications for details). Before moving into neuroscience, I graduated with a BA in Natural Sciences from Cambridge where I did courses and research in both molecular biology and theoretical chemistry, and I continue to be interested in interdisciplinary research spanning the biological and physical sciences.

mGPLVM – Beyond the Euclidean Brain (Bernstein Conference 2020)