Vikash Mansinghka

MIT Probabilistic Computing Project
@vmansinghka

Vikash Mansinghka is a research scientist at MIT, where he leads the Probabilistic Computing Project. Vikash holds S.B. degrees in Mathematics and in Computer Science from MIT, as well as an M.Eng. in Computer Science and a PhD in Computation. He also held graduate fellowships from the National Science Foundation and MIT’s Lincoln Laboratory. His PhD dissertation on natively probabilistic computation won the MIT George M. Sprowls dissertation award in computer science, and his research on the Picture probabilistic programming language won an award at CVPR. He served on DARPA’s Information Science and Technology advisory board from 2010-2012, and currently serves on the editorial boards for the Journal of Machine Learning Research and the journal Statistics and Computation. He was an advisor to Google DeepMind and has co-founded two AI-related startups, one acquired by Salesforce.com in 2012 and one acquired by Tableau in 2018.

Probabilistic programming and meta-programming in Clojure

Do you want to learn modern data science, without having to first learn advanced mathematics and statistics? The MIT Probabilistic Computing Project is developing new, open-source, Clojure-based probabilistic programming languages: Metaprob and BQL. BQL is an SQL-like language that aims to make it possible for millions of developers to solve challenging data science problems, by extending ordinary database concepts. Metaprob is a probabilistic meta-programming language that aims to make it possible to teach anyone who can learn Clojure the key principles of probabilistic artificial intelligence. This talk will give a gentle introduction to both BQL and Metaprob, describe ways to contribute to both projects, and showcase applications in improving mental health and respiratory care for children.