My background is theoretical physics. I hold a PhD in string theory, and I did extensive research work in quantum gravity and quantum field theory. My expertise, though, is in the statistical modeling of quantum black holes, specifically in the connection between black hole entropy and number theory.

Today I am interested in machine learning and data science. Physicists are interested in running experiments and seeing what the universe outputs. Intriguingly, I find that running a machine learning algorithm on a computer is a very similar experience. It is like poking a universe that can fit in your lap and seeing what comes out of it. Except that I can run this experiment as many times as I like it!

My goal is to bring physics insights and apply them in this field. But first, let’s start with the fundamentals and basic building blocks of machine learning and data science.