Welcome!
My research explores the intersection of law and game theory, with a focus on developing mathematically sound ways to make legal decision-making more accurate, consistent, and fair. Toward that end, I have devised a new form of arbitration and designed a new committee selection method in order to produce outcomes that better reflect what the median or average qualified decision-maker would award. My most recent work examines how advances in artificial intelligence and machine learning can improve the judicial process.
AI AND THE FUTURE OF JUDGING
Robot Twiqbal (working paper)
Accuracy and the Robot Judge, 25 J. App. Prac. & Process 1 (2025) [SSRN] [Selected for plenary presentation, Thirteenth Annual Junior Faculty Federal Courts Workshop]
A New Form of Arbitration
Running it Twice (or Thrice): Double-Header and Triple-Header Baseball Arbitration [SSRN] [Finalist, 2020 MIT Sloan Sports Analytics Conference Research Paper Competition] [Video]
A New Committee Selection Method
Randomly Selected Representative Committees (with Josep E. Peris & Begoña Subiza) (working paper) [SSRN]
Divide and Conquer: How the Democrats Can Maintain Control of the Ninth Circuit, Harvard Law & Policy Review Blog (Sept. 25, 2019) [SSRN]
The Rank-Order Method for Appellate Subset Selection, 93 Notre Dame L. Rev. Online 17 (2017) [SSRN] [Video]
Ending the Reign of Slot Machine Justice,57 N.Y.U. Ann. Surv. Am. L. 291 (2000) [SSRN] [Winner, 2001 NYU Annual Survey of American Law “Student Note of the Year” award]