I’m a third year PhD student in Harvard’s Theory of Computation and ML Theory groups. I’m advised by Leslie Valiant and supported by an NSF Graduate Research Fellowship. Previously, I undergraduated in math at Princeton.

I’m interested in theoretical computer science broadly. In particular, I study the interplay between algorithms, learning, and strategic behavior.

bedelman@g.harvard.edu | Google Scholar | he/him

## News

Chara Podimata, Yo Shavit, and I organized a tutorial at FAccT 2021 called **How to Achieve Both Transparency and Accuracy in Predictive Decision Making: An Introduction to Strategic Prediction**!

## Publications

**Causal Strategic Linear Regression**

with Yonadav Shavit and Brian Axelrod

*ICML 2020*

**The Multiplayer Colonel Blotto Game**

with Enric Boix-Adserà and Siddhartha Jayanti

*EC 2020*

**SGD on Neural Networks Learns Functions of Increasing Complexity**

with Preetum Nakkiran, Gal Kaplun, Dimitris Kalimeris, Tristan Yang, Fred Zhang, and Boaz Barak

*NeurIPS 2019 (Spotlight)*

**Matrix Rigidity and the Croot-Lev-Pach Lemma**

with Zeev Dvir

*Theory of Computing, 2019*