I am an assistant professor in the Khoury College of Computer Sciences at Northeastern. My group combines probabilistic programming with deep learning to develop probabilistic models for machine learning, data science, and artificial intelligence. I am one of the creators of Anglican, a probabilistic programming system that is closely integrated with Clojure. I am currently developing of Probabilistic Torch, a library for deep generative models that extends PyTorch.
DEC 2018 ∙ Two papers by Babak Esmaeili will appear at AISTATS 2019: 1. Structured Disentangled Representations [arXiv] (with Hao Wu, Sarthak Jain, and Alican Bozkurt) 2. Structured Neural Topic Models for Reviews [arXiv].
OCT 2018 ∙ A draft of our book An Introduction to Probabilistic Programming is now publicly available [arXiv]. This book is intended as a graduate-level introduction to probabilistic programming languages and methods for inference in probabilistic programs.
OCT 2018 ∙ I co-chaired the International Conference on Probabilistic Programming (PROBPROG 2018).
AUG 2018 ∙ The NSF has funded our work on deep probabilistic models for individual variation in neuroimaging experiment! Award #1835309, co-investigators Ajay Satpute, Benjamin Hutchinson, Jennifer Dy, and Sarah Ostaddabas.