About Me

I’m Andrew! I’m an individual who is enthuastic about using data and ML/AI to solve problems and make an impact. Until recently, I was a Research Data Scientist at Meta, where I worked on capacity, efficiency and productivity within their Data Infrastructure org. Prior to that, I completed my PhD in Statistics at Columbia University, supervised by Prof. Tian Zheng. My research has been published in venues such as NeurIPS and JMLR.

My research interests focused around machine learning methods for network embedding methods, examining these from a statistical perspective and seeking methodological improvements of these methods. I’m also interested in the implications of using the learned embedding vectors for different downstream tasks in machine learning. See my Research page for a more detailed breakdown about my thoughts and interests. While I’m no longer attached to academia, I’m still interested in persuing research if the right problem arises.

Prior to beginning my PhD, I completed my undergraduate (BA) and masters (MMath) degrees in Mathematics at Kings’ College, University of Cambridge. In my (vanishing amounts of) spare time, I like to cook, bake and go rock climbing and bouldering.