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Joonhyuk Ko
jk9737 [at] princeton.edu

Hi, I'm Joon. I’m an incoming PhD student at Princeton University, where I will be working with Lydia T. Liu. I did my undergrad at University of Virginia, where I studied computer science and math and worked with Ferdinando Fioretto. I also spent a wonderful summer in 2025 as a research intern at Carnegie Mellon University, advised by Steven Wu.

I work on the societal impact of AI, particularly in high-stakes decision-making settings. I'm interested in algorithmic fairness, differential privacy, optimization, and uncertainty quantification. My research is supported by the NSF Graduate Research Fellowship. Fun fact: my Erdős number is 3.


News


Publications

Provably Label-Efficient Conformal Prediction
(α − β) Andrew Ilyas, Joonhyuk Ko, Jingwu Tang, Steven Wu, and Jiahao Zhang
International Conference on Machine Learning (ICML), 2026
Fairness Issues and Mitigations in (Differentially Private) Socio-Demographic Data Processes
Joonhyuk Ko, Juba Ziani, Saswat Das, Matt Williams, and Ferdinando Fioretto
AAAI Conference on Artificial Intelligence (AAAI), 2025
Oral Presentation (Top 5%)
Optimal Allocation of Privacy Budget on Hierarchical Data Release
Joonhyuk Ko, Juba Ziani, and Ferdinando Fioretto
ArXiv Preprint, 2025
(α − β) denotes alphabetical author ordering