Here you’ll find various things I’ve generated – research papers, random thoughts, and other creative outputs. All opinions are my own and not those of my employer or collaborators.  


Mathematical elegance, figuring out how things work, and clear thinking are some of the things that interest me.

I received my B.S. and Ph.D in mathematics from Caltech and MIT. I was subsequently a Research Assistant Professor at the Simons Center for Geometry and Physics (2011-2014) and then a Visiting Assistant Professor at Michigan State University (2014-2017). During these years, my research interests expanded into high-energy physics, where I investigated mathematical problems underlying quantum field theory that have been extensively misformulated or overlooked. Most notably, my work provides a formulation of perturbative path integrals that simplifies and corrects prevailing conventional treatments, from which I proceed to clarify perturbative and nonperturbative foundations of  Yang-Mills theory that have been lacking in deeper mathematical scrutiny.

Since mid-2017, I’ve been working on machine learning in industry. Presently, I am a research engineer at DeepMind focused on advancing the field deep learning.