Research

Broadly Thinking About

The intersections of micro theory and computer science.

How do no-regret algorithms act in pricing games? How do reinforcement learning algorithms act? When are supracompetitive prices collusive, and when are they just misspecification.

Specifically

I’ve derived necessary and sufficient conditions for extensive form coarse correlated equilibria to be equivalent to Nash equilibria. I’ve derived sufficient conditions for normal fome games, but they are not yet tight. I’m working on it!

Thinking, along with Omar Andujar about stable matching under memory constraints, and how we can derive a price of anarchy when we don’t have strategy proofness.

How would a monopolist trying to second-degree price discriminate under an uncertain state? Can we derive guarantees of how good or bad they’d do? I’m not sure yet!

Research Statement

Check back when I’m on the job market.

Some math I’ve been working on

$$ \mathbb{E}_{\substack{(h,S_{-i})\sim\mu \ d_c\sim\delta_c}} \Bigl[u_i\bigl(h,\sigma_i,S_{-i},d_c\bigr)\Bigr] \ge \mathbb{E}_{\substack{(h,S_{-i})\sim\mu\ d_c\sim\delta_c}} \Bigl[u_i\bigl(h,S’_i,S_{-i},d_c\bigr)\Bigr] $$

for all $S’_i$ and for all

$$ \mu \in \Delta \Bigl((h,S_{-i}) : h\in I_i,\ S_{-i}\in\Sigma_{-i} \text{, and } \mathbb{P} (h \mid \sigma_i S_{-i} \delta_c) > 0 \Bigr) $$

(updated 11/03/2025)