Before joining the University of Oxford, I have been 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 Probability Theory under the supervision of Ramon van Handel.
Here is my Curriculum Vitae.
My research interests lie at the intersection of Probability, Statistics, and Computer Science. I am interested in the investigation of fundamental principles in high-dimensional probability, statistics and optimization to design computationally efficient and statistically optimal algorithms for machine learning.
As a Fellow at the Alan Turing Institute London, I have been involved with the following activities:
I am a Co-Investigator for the Imperial-Oxford StatML Centre for Doctoral Training (CDT). I am a member of the Bernoulli Society, Institute of Mathematical Statistics (IMS), and European Laboratory for Learning and Intelligent Systems (ELLIS). I am an alumnus of the Yale Institute for Network Science and Princeton Statistical Laboratory.
At the University of Oxford, I regularly organize reading groups on learning theory and statitical optimization:
Since 2018, I have been teaching Algorithmic Foundations of Learning, for which I received the 2019 Oxford MPLS Teaching Award.
In Spring 2021, I taught Simulation and Statistical Programming. In Spring 2018, I taught Advanced Simulation Methods.
Since 2017, I have been teaching probability theory, statistics, and graph theory as part of my tutorial duties at University College Oxford.
I regularly contribute to Open Days. Here is a 2021 video to introduce statistics to high-school students via machine learning and the multi-armed bandit problem.
At Yale University, 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. I was a member of the Yale Postdoctoral Association, and for three years in a row, from 2015 to 2017, I organized 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.
At Princeton University, in 2013 I received the Excellence in Teaching Award from the Princeton Engineering Council while serving as head teaching assistant for ORF 309 (Probability and Stochastic Systems) at Princeton University. I was also a fellow of the McGraw Center for Teaching and Learning at Princeton University.