Jabari Hastings

I am a PhD candidate in Computer Science at Stanford University, advised by Omer Reingold and Aviad Rubinstein. I am a member of the CS Theory Group and my research spans computational social choice, mechanism design, and learning theory. I am particularly interested in designing algorithms with provable fairness guarantees.

I am no stranger to Stanford, having studied Mathematics and Computer Science here as an undergrad. I was extremely lucky to be advised by Jan Vondrák and Mary Wootters.

I enjoy teaching, and through JamCoders I have had the opportunity to mentor many amazing high school students back home in Jamaica.

When I am not thinking about a problem, I spend time swing dancing, playing tennis, hiking, and playing music on the steelpan.

Research overview

My recent work explores how closely ranking-based mechanisms can approximate full-information outcomes (via metric distortion) and the performance of strategyproof mechanisms in facility location. A unifying theme is establishing approximation guarantees across broad classes of social-cost objectives—often simultaneously.

1. Fair metric distortion for matching with preferences
   Jabari Hastings and Prasanna Ramakrishnan
   Web and Internet Economics (WINE) 2025
2. Optimal Metric Distortion for Learning-Augmented Matching on the Line
   Jabari Hastings and Marena Richter
   In Submission, 2026
3. Strategic Facility Location with $p$-Norm Social Costs
   Jabari Hastings
   In Submission, 2026
4. Maximum-Cost Strategic Facility Location: The Limits of Randomization
   Jabari Hastings and Misha Ivkov
   In Submission, 2026

For further details and additional work, see my Research page.