Jabari Hastings

I am a PhD candidate in Computer Science at Stanford University, advised by Omer Reingold and Aviad Rubinstein. My research spans mechanism design, social choice and learning theory. I am especially interested in designing algorithms with provable fairness guarantees.

I am no stranger to the CS Theory Group, having studied Mathematics and Computer Science as an undergrad at Stanford. 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 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. Optimal Metric Distortion for Learning-Augmented Matching on the Line
   Jabari Hastings and Marena Richter
   Web and Internet Economics (WINE) 2026
2. Fair metric distortion for matching with preferences
   Jabari Hastings and Prasanna Ramakrishnan
   Web and Internet Economics (WINE) 2025
3. Strategic Facility Location with $p$-Norm Social Costs
   Jabari Hastings
   In Submission
4. Maximum-Cost Strategic Facility Location: The Limits of Randomization
   Jabari Hastings and Misha Ivkov
   In Submission

For further details and additional work, see my Research page or my Google Scholar profile.