Abraham Othman
Contact Info
About Me
Call me Abe. I'm a first-year PhD Student in the Computer Science
Department at the School of Computer Science at Carnegie Mellon. My
advisor is the brilliant Tuomas Sandholm, which makes me part of the AMEM research
group, a bunch of inveterate gamblers with a computing problem.
This is what I looked like on my first day of graduate school.
I like probability, markets, design, and market design. If I were a Springer Graduate Text in Mathematics, I'd be J.L. Doob's Measure Theory. My former roommate Stephen Dawson-Haggerty does Systems at Berkeley and is a pretty cool guy.
Things I Do
I run the Game Theory Discussion Group. I'm also part of Dec/5 and FreeCSD, the semi-secret social organizations of SCS and CSD, respectively. I figured out how to make a door label, and then I helped rebuild the free food cam.
When I'm at work I like to listen to new music. You can check out my hype machine page to see what I'm currently digging.
Previously
I previously attended Harvard, where I managed to graduate with a
degree in Applied Math without ever taking a course offered by the eponymous department. I did, however, complete graduate coursework in Harvard's fine Computer Science,
Economics, and Comparative Literature departments. My undergraduate advisor was David Parkes and I also worked with Uli Doraszelski. I guided Adams House to several years of odious Intramural performance, a stretch of humiliating defeats broken only by the 2006 Men's A House Crew boat.
I grew up in Ann Arbor, Michigan, which gave me an appreciation for college sports and an ability to find humor in the cruel vicissitudes of fate.
Publications
Corwin, I. and Othman, A. 2008. Time
Inconsistency and Uncertainty Aversion in Prediction Markets, at the Third Workshop on Prediction
Markets, in conjunction with the ACM Conference on Electronic Commerce (EC). Download preprint.
Starting from first principles we derive a method for detecting price
biases in prediction
market data. Using this method on Tradesports contracts from the 2005-06
NBA season, we
demonstrate that trades executed in the last hour of trading have a
significant longshot price
bias, while trades occurring earlier do not. We present a new
theoretical model which uses
uncertainty aversion to explain our findings.
Othman, A. and Sandholm, T. 2008. Beyond the
Revelation Principle: Manipulation-Optimal Mechanisms,
presented at the Third World Congress of the Game Theory
Society (GAMES 2008).
Othman, A. 2008. Zero-Intelligence Agents in
Prediction Markets, in Proceedings of the
7th International Conference on Autonomous Agents and Multiagent Systems
(AAMAS). Download pdf.
Conlee B., Othman, A., and Yetter, C. 2007. What to Feed a Gerrymander. The UMAP Journal 27(3): 261-280. Download preprint.
We construct a novel agent-based model of prediction markets in which putative human qualities like learning, reasoning, and profit-seeking are absent. We show that the prices which emerge from a market populated by a class of distinctly inhuman agents, Zero-Intelligence agents with diffuse beliefs, replicate the findings of empirical market studies. We use this result to argue against the prevailing descriptive theories of price formation in prediction markets, which have stressed the role of expert, rational participants.
Conlee B., Othman, A., and Yetter, C. 2007. What to Feed a Gerrymander. The UMAP Journal 27(3): 261-280. Download preprint.
This was Harvard's winning entry in the 2007 Mathematical Contest in Modeling (MCM). The prompt was to design an algorithm to simply and fairly redistrict states, and to demonstrate our method using the state of New York. Our solution interpreted the problem as an issue of large-scale combinatorial optimization. Our paper earned an "Outstanding" rating (top 1%) and won a prize from INFORMS, an MCM sponsor, as their selection for best paper.