My passion is to apply artificial intelligence and machine learning to build products that people love to use.
As an engineer in the ads ranking team at Facebook my work starts with research: understanding the state of the art in AI and inventing new machine learning models. Next I will drive the engineering work to make these ideas a reality in production systems: scaling to the billions of users on Facebook is often a challenge and requires close collaboration with infrastructure teams around the company. Finally, I will run experiments to test how my hypothesis hold up in the real world.
Before Facebook, I did my PhD in machine learning at the University of Cambridge on Bayesian non-parametric methods for time series analysis. I’ve worked for Microsoft Research on recommender systems, probabilistic programming languages and graphical models; I’ve lead the AI efforts at a startup called Rangespan and worked on automated bidding strategies at Google.
Machine learning, Bayesian methods, neural networks, ads and statistics