Yi-Hsiu Chen
I am an applied cryptographer at Coinbase. Previously, I was a research scientist in the Ads Core ML team at Facebook.
I completed my Ph.D. in theoretical cryptography at Harvard University, advised by Salil Vadhan. Before that, I studied physics at National Taiwan University and computer science at Columbia University.
Email: yihsiu@alumni.harvard.edu · LinkedIn · GitHub
Projects
Research
My work spans applied and theoretical cryptography, including zero-knowledge proofs, secret sharing, pseudorandomness, and differential privacy.
During a visit to Academia Sinica in Taiwan in 2015–2016, I was hosted by Kai-Min Chung, who introduced me to quantum information.
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Yi-Hsiu Chen and Yehuda Lindell.
Optimizing and Implementing Fischlin’s Transform for UC-Secure Zero Knowledge
IACR Communications in Cryptology, 1(2), 2024. [journal] [ePrint, revised March 2026] -
Yi-Hsiu Chen and Yehuda Lindell.
Feldman’s Verifiable Secret Sharing for a Dishonest Majority
IACR Communications in Cryptology, 1(1), 2024. [journal] [ePrint] -
Rohit Agrawal, Yi-Hsiu Chen, Thibaut Horel, and Salil Vadhan.
Unifying Computational Entropies via Kullback–Leibler Divergence
CRYPTO 2019. [ePrint] -
Yi-Hsiu Chen, Mika Göös, Salil Vadhan, and Jiapeng Zhang.
A Tight Lower Bound for Entropy Flattening
CCC 2018. [paper] -
Yi-Hsiu Chen, Kai-Min Chung, and Jyun-Jie Liao.
On the Complexity of Simulating Auxiliary Input
EUROCRYPT 2018. [ePrint] -
Yi-Hsiu Chen, Kai-Min Chung, Ching-Yi Lai, Salil Vadhan, and Xiaodi Wu.
Computational Notions of Quantum Min-Entropy
Preprint, 2017. [arXiv] -
Mark Bun, Yi-Hsiu Chen, and Salil Vadhan.
Separating Computational and Statistical Differential Privacy in the Client-Server Model
TCC 2016-B. [ePrint] [slides]
Dissertation: Computational Notions of Entropy: Classical, Quantum, and Applications (May 2019).