BU MCS 200C usmn[at]bu[dot]edu (646) 73two 8628
[CV]


Ben Usman
I'm a firstyear PhD student in the Image and Video Computing group at Boston University advised by Professor Kate Saenko. I mostly work on applying deep learning to model natural language parse trees and graphs in general. Also, I recently started diving into deep Bayesian generative models such as VAEs, adversarial networks and learning about how they relate to domain adaptation.
Before that, I was mostly working on machine learning for natural language processing since my BSc in Applied Mathematics and Physics at Moscow Institute of Physics and Technology (MIPT). And I am still interested in natural language understanding, information representation and reasoning over structured data.
I also got an additional research experience during my MSc in Applied Mathematics and Computer Science at Skoltech and MIPT which involved studying numerical methods for linear algebra (e.g. multigrid, fast multipole method) and Bayesian methods.
I also took (and liked) graduatelevel optimization and statistical learning theory. And, I have always been very interested in applying Bayesian methods in decision making and problems that involve active information acquisition in general, but unfortunately, I did not encounter a project to get any good understanding of it or handson experience, (yet!)
My research dream goal is dawn of AIassisted science in nearest future :)
In reverse chronological order I did the following:
 worked as a visiting grad student at UML (Spring 2016) and at MIT (Fall 2015)
 during my MSc, I worked with Ivan Oseledets at Skoltech on numerical linear algebra algorithms (Spring 2015)
 my BSc graduation project was on applications of Deep Learning features to Named Entity Recognition during my internship at ABBYY (2014)
I also did a bunch of backend web development in Python a while ago.
Disclaimer: rarely, people find me arrogant, but that is due to translation issues  believe me, I'm a very kind person who just really likes learning new stuff from those around me.
