Eric Neyman

neyman.eric [at] gmail [dot] com

I am a researcher at the Alignment Research Center (ARC), where I'm working toward a formal framework for the mechanistic interpretability of neural networks.

Before joining ARC, I was a PhD student in theoretical computer science at Columbia University, where I was advised by Tim Roughgarden. I wrote my thesis, Algorithmic Bayesian Epistemology, on reasoning about uncertainty under constraints: constraints on information, communication, and computation, as well as constraints imposed by the strategic behavior of experts. 

Links:

Papers and publications:

Rafael Frongillo, Eric Neyman, Bo Waggoner

In ACM Conference on Economics and Computation (EC), 2023

Eric Neyman, Tim Roughgarden

In ACM Conference on Economics and Computation (EC), 2022

Paul Christiano, Eric Neyman, Mark Xu

Eric Neyman, Tim Roughgarden

In Operations Research and ACM Conference on Economics and Computation (EC), 2021

Eric Neyman, Tim Roughgarden

Eric Neyman, Georgy Noarov, S. Matthew Weinberg

In ACM Conference on Economics and Computation (EC), 2021

Eric Neyman, Tim Roughgarden

In AAAI Conference on Artificial Intelligence (AAAI), 2022

Tomer Ezra, Michal Feldman, Eric Neyman, Inbal Talgam-Cohen, S. Matthew Weinberg

In Proceedings of the 60th Annual IEEE Symposium on Foundations of Computer Science (FOCS), 2019.

Liljana Babinkostova, Jackson Bahr, Yujin Kim, Eric Neyman, Gregory Taylor

In Journal of Number Theory, Vol. 201 (2019).

Jackson Bahr, Yujin Kim, Eric Neyman, Gregory Taylor

In Rose-Hulman Undergraduate Mathematics Journal, Vol. 19: Iss. 1 (2018).

Eric Neyman, 2015