Prior to joining the University of Oxford, I was a Lecturer in the Computer Science department at Yale University and a Postdoctoral Associate at the Yale Institute for Network Science, hosted by Sekhar Tatikonda.
I have a Ph.D. in Operations Research and Financial Engineering from Princeton University, where I worked in Applied Probability under the supervision of Ramon van Handel.
Here is my Curriculum Vitae.
My research interests lie at the intersection of Applied Probability, Statistics, and Computer Science. I am interested in the investigation of fundamental principles to perform scalable inference, learning, and optimization in high-dimensional models, and in the design and analysis of algorithms in distributed Machine Learning, with applications to graphical models and Monte Carlo methods.
In Fall 2017 I am running an introductory reading group on optimization for machine learning. Here are the notes.
In Spring 2018 I will be teaching Advanced Simulation Methods at Oxford (Part C/MSc).
While at Yale, in Fall 2016 I served as the Head Instructor for CS50 — Introduction to Computing and Programming — taught jointly with Harvard University. This was a coverage on the Yale Daily News. Here is the intro class in Machine Learning and Python, or its VR version.
From 2015 to 2017 I supervised a group of senior students on research projects in Machine Learning, investigating the development of algorithms for natural language processing, sparse regression, and distributed optimization.
I was a member of the Yale Postdoctoral Association, with the goal to facilitate and promote teaching experiences for postdocs in the sciences. On April 2, 2017, we hosted the third edition of the Julia Robinson Mathematics Festival at Yale, a celebration of ideas and problems in mathematics that enable junior high and high school students to explore fun math in a non-competitive setting.
While at Princeton, I repeatedly served as teaching assistant for ORF 309 (Probability and Stochastic Systems) taught by Prof. Erhan Çınlar. ORF 309 is considered one of the most challenging classes offered at Princeton University, and it is taken by approximately 150 students, 80% of which are undergraduate. In fall 2012 I was appointed head teaching assistant for the class and I received the 2013's Excellence in Teaching Award from the Princeton Engineering Council.
I was also a fellow of the McGraw Center for Teaching and Learning at Princeton University.