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Here's a slightly out of date resume.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 2012-16 I was in the Ph.D. program at UC Berkeley. I attended the Masters of Logic Program at the ILLC at the University of Amsterdam from 2009 to 2011, where I studied mathmatical logic and AI. I graduated with an honors AB in Philosophy and Mathematics from Harvard University in 2009.

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