Vikash K. Mansinghka
I am currently a Research Scientist with
Initiative, where I lead the Probabilistic Computing Project.
We are supported by
MIT's Computer Science and
Artificial Intelligence Laboratory (especially Google's "Rethinking
AI" project), the Department of Brain & Cognitive Sciences, and
Harvard's School of Engineering and Applied Sciences (where I am a
Visiting Fellow). I am also involved in consulting and
advisory relationships with industry, and co-founded a startup that was ultimately acquired by Salesforce.com in 2012. I have served on DARPA's Information Science and Technology (ISAT) advisory board, and currently serve on the Editorial Board for the Journal of Machine Learning Research.
I received my PhD in 2009 from MIT, advised by
Professor Joshua Tenenbaum.
I build probabilistic computing systems that exploit uncertain knowledge to learn from data, infer its probable causes, make calibrated predictions and choose effective actions. I also study the computational principles and building blocks needed to design, implement and analyze these systems, drawing on and contributing to an emerging integration of key ideas from probability theory and computer science. This research includes work on machine learning and artificial intelligence fundamentals, as well as applications to modeling human cognition and to intelligent data analysis.
So far, this work has yielded new general-purpose probabilistic programming technology and intentionally stochastic (but still digital) hardware for real-time Bayesian inference. It has also yielded academic and commercial Bayesian database systems that automate the analysis of high-dimensional data tables.