It all started when…
My background is in maths and computer science. I become interested in artificial intelligence between my undergraduate and masters, particularly to the possibilities of having machine learning agents take the cognitive load of processing increasing amounts of data.
Studying artificial intelligence at Imperial College London opened my eyes to neural networks and Bayesian inference. I followed this passion with a PhD in machine learning for spatio-temporal data and studied probabilistic models of time series, discrete data, and variational inference. This took me to David Blei's lab at Princeton who introduced me to causal analysis and latent variable recommendation models.
I now combine all these elements in my job as a research scientist at Netflix where I continue to publish and work with other scientists to develop new machine learning methods.