About me

I am a Postdoctoral Research Associate in the Gamze Gürsoy’s lab, where I have been working since March 2022. I received my Ph.D. from the Department of Mathematical Science at Seoul National University, South Korea, advised by Jung Hee Cheon.

My primary research focuses on practical applications of cryptosystems, especially in homomorphic encryption, privacy-preserving machine learning, and genomic data privacy. I work extensively with Fully Homomorphic Encryption (FHE), optimizing FHE schemes algorithmically and developing algorithms to enable non-arithmetic operations within FHE. In privacy-preserving machine learning, I adapt machine learning algorithms to FHE-compatible formats, utilizing polynomial approximation techniques to achieve secure and efficient computation. My research in genomic data privacy emphasizes designing FHE-based frameworks that enable secure transformations of conventional genomic applications, protecting sensitive genomic information. I am also dedicated to advancing functional encryption by creating schemes that offer enhanced efficiency and functionality.

News and Upcoming Events

• [Feb, 2025] The paper “Secure and Scalable Gene Expression Quantification with pQuant” is published in Nature Communications (link).

• [Nov, 2024] The paper “Fully Encrypted Machine Learning Protocol using Functional Encryption” is uploaded to ePrint Archive. We proposed fully encrypted fE-based PPML protocol, which supports the evaluation of arbitrary functions over encrypted data with no information leakage during computation, for the first time (link).

• [Oct, 2024] The paper “Ultra-Secure Storage and Analysis of Genetic Data for the Advancement of Precision Medicine” is accepted for publication in Genome Biology.