Email
omangoubi@wpi.edu
Office
Unity Hall 385
Affiliated Department or Office
Education
BS Mathematics, and Engineering Sciences-Electrical, Yale University 2011
PhD Applied Mathematics, Massachusetts Institute of Technology (MIT) 2016

My research is focused on the design and analysis of fast algorithms for machine learning, optimization and data science. I am especially interested in Markov chain and stochastic gradient-based optimization and sampling algorithms.  These algorithms are used to rapidly explore a high-dimensional or non-convex function or probability distribution in applications such as deep learning and Bayesian statistics.  I am also very interested in the application of these algorithms to problems in machine learning, data science, theoretical computer science, and statistics.  I am looking forward to working with students at the PhD, masters, and undergraduate levels who are interested in the mathematical, computational, or statistical aspects of machine learning and data science.  I am currently teaching Statistical Methods for Data Science (DS502/MA 543), and I look forward to teaching both undergraduate and graduate courses in Mathematics and Data Science at WPI.

Scholarly Work