I am an first year PhD student under Cambridge-Tuebingen PhD Felloship. I am working with Bernhard Schölkopf at the Max Planck Insitute for Intelligent Systems in Tübingen and Ferenc Huszar at University of Cambridge.
My research interest lies in the intersection of causal inference and machine learning. Particularly, during the first year of my PhD, I aim to work on the topic of Causal Representation Learning. Deep neural network methods have proved to be very efficient at learning statistical association within data. However, it is becoming clear that they fail to learn causally valid representations, which is essential for robust inference and reasoning. Therefore I am interested in developing new techniques for training neural networks such that they learn about the invariant causal structure behind the data.
Previously I was a Msc in Machine Learning student at University College London (UCL) and studied Mathematics (Bsc + MMath) at University of Cambridge. Also at a previous life, I worked as a Quantitative Strategist at Goldman Sachs International.