Steven Jecmen

In March 2024, I joined Tower Research Capital as a quantitative trader. [CV]

I previously completed a PhD in the Computer Science Department at Carnegie Mellon University, where I was co-advised by Fei Fang and Nihar Shah. During my PhD, my research focused primarily on issues of fraud and malicious behavior in settings where people evaluate things. Important decisions are often made based on human evaluations, but in many cases, these decision-making processes are vulnerable to fraud on the part of the evaluators or other participants. My work proposes practical methods that provide robustness to various forms of such malicious behavior. More broadly, my research interests include game theory, optimization, statistics, and related areas.

A specific application where my research has had an impact is in the area of scientific peer review. As one example, a major concern in this setting is collusion between reviewers and authors. We provide efficient algorithms for finding high-quality randomized assignments, thereby limiting the probability that a colluding reviewer-author pair succeeds at manipulating the paper assignment. Our main algorithm has been implemented at OpenReview.net and deployed for paper assignment at several venues, including the AAAI 2022-2023 and KDD 2023 conferences.

Before coming to CMU, I graduated from the University of Michigan with a BSE in Computer Science and a Minor in Economics. There, I was supervised by Michael Wellman and did research on techniques for empirical game theory.

During the summer of 2023, I worked at Tower Research Capital as a quantitative trader intern. I previously worked at Citadel and at CME Group as a software engineering intern.