Email: elohn [at] cs [dot] cmu [dot] edu

About

Hello, my name is Evan Lohn. I am a PhD student (began Fall 2021) in the Computer Science Department at Carnegie Mellon University advised by Marijn Heule and Jeremy Avigad.

In the past, I worked with Pieter Abbeel at the BAIR lab on applications of deep unsupervised learning to image compression. I'm still very much interested in potential applications of deep unsupervised learning (especially for theorem proving), but more recently I've been approaching theorem proving from the perspective of automated reasoning and interactive theorem provers like Lean. I'm broadly interested in automated and interactive theorem proving, and I hope to contribute to the work being done in the SAT and Lean communities soon!

Research Publications

• Jonathan Ho, Evan Lohn, and Pieter Abbeel
  Compression with flows via local bits-back coding (2019) [arxiv]
  In NeurIPS 2019
• Evan Lohn, Chris Lambert, and Marijn Heule
  Compact Symmetry Breaking for Tournaments (2022) [paper] [code]
  In FMCAD 2022