Much of my research involves the design and analysis of Markov chain Monte Carlo algorithms and related optimization algorithms used in Statistics, Data Science and Machine Learning applications. In my research I use mathematical tools from probability and differential geometry.
In 2016 I received my PhD in Applied Mathematics at MIT, advised by Alan Edelman (MIT Mathematics department) and also working with Natesh Pillai (Harvard Statistics department). From 2017-2019 I was a postdoctoral researcher in Computer Science at EPFL, advised by Nisheeth Vishnoi (Yale, previously at EPFL). From 2016-2017 I was a CANSSI postdoctoral fellow at the University of Ottawa Mathematics and Statistics department working with Aaron Smith, where I taught a Statistics and Probability course for engineering majors.
Undergraduate and Graduate Mathematics and Data Science Courses
Statistical Methods for Data Science (DS502/MA543), WPI, Fall 2019
Probability & Statistics for Engineers (MAT2377), Univ. of Ottawa, Winter 2017
K-12 Mathematics education
Instructor, MITxplore weekly Mathematics enrichment class for disadvantaged youth, Spring+Fall 2013, Spring+Fall 2014, Spring 2015
Directed Reading Program mentor for MIT Math majors, Winters 2014 and 2015