Adam Lesnikowski

Hello! This is the website of Adam Lesnikowski. I am very interested in machine learning, statistical learning theory, active learning, neural networks and AI, especially applied to computer vision and other web-scale data problems.


As of January 2017, I've joined Nvidia in Santa Clara, CA as a senior software perception engineer, working on machine learning research for autonomous vehicles. I'm very excited to be a part of this brilliant group!


Here's a slightly out of date resume.


From 2012 to 2016 I was at the Ph.D. program at UC Berkeley, where I was worked on set theory, mathmatical logic, large cardinals and a bit on rationality. From 2009 to 2011, I was at UvA's Institute for Logic, Languague and Computation MSc program studying mathmatical logic, theoretical CS and AI. From 2004-2009, I was at Harvard University, where I studied mathematics and philosophy.

Selected Past Work

Deep Active Learning, talk at the GPU Technology Conference, March 2018.

Predicting Prices for House Shares using Deep Convolutional Neural Networks, with Rong Yuan, Genevieve Patterson, 2016.

How Much Did it Rain?: Predicting Real Rainfall Totals Based on Polarimetric Radar Data, paper of a project with Peter Bartlett and Alexei Efros, 2015.

NP-Completeness Papers by Cook, Levin and Karp, P =?NP, and a Lost Letter, slides with Justine Sherry, UC Berkeley CS 294, 2014.

A Geometric Interpretation of the Metaphysics of the Tractatus, paper based on project with Professor Paolo Mancosu, 2014.

Reasoning About an Ordering of Theories, my undergraduate thesis, with Warren Goldfarb, on a modal logic that captures all correct reasoning about mathematical interpretations.

Contact Info

Email: first name dot last at