Kiran Tomlinson

Kiran Tomlinson

PhD Candidate, Computer Science

Cornell University


Iā€™m a Computer Science PhD candidate at Cornell University advised by Jon Kleinberg and collaborating with Johan Ugander on problems around instant-runoff voting. More broadly, Iā€™m interested in modeling and understanding human behavior (especially choices) through algorithmic and machine learning methods. During my PhD, I’ve interned at Microsoft Research with Jennifer Neville on recommendations in networks and at Microsoft’s Office of Applied Research with Longqi Yang and Mengting Wan on multi-organization recommendation. In Winter and Spring 2023, I was a visiting instructor at Carleton College teaching Data Structures and Mathematics of Computer Science.

When away from my desk, I spend my time playing guitar, building 8-bit computers, playing video games, biking, listening to music, flying quadcopters, bouldering, and playing pool. I have additional interests in spaceflight, Premier League football, and Formula 1.

Recent news

šŸ“ Dec ‘23 Our paper on consider-then-choose ranking models was accepted as an extended abstract to AAMAS ‘24!

šŸ“ Dec ‘23 Our paper on the moderating effect of instant runoff voting was accepted to AAAI ‘24!

šŸ—£ Aug ‘23 Gave a talk on instant runoff voting at the Cornell CS Theory Seminar.

šŸ“ Aug ‘23 Our paper on networked choice was accepted to Network Science!

šŸ—£ Aug ‘23 Gave a talk at KDD on recommendation with temporal network objectives.

All news

Collaboration Network

People are red, papers are blue.

Recent Papers

(2024). The Moderating Effect of Instant Runoff Voting. AAAI.

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(2024). Bounding Consideration Probabilities in Consider-Then-Choose Ranking Models. arXiv.

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(2023). Graph-based Methods for Discrete Choice. Network Science.

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(2023). Workplace Recommendation with Temporal Network Objectives. KDD.

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