Eunsang Lee

Eunsang Lee serves as an Assistant Professor in the Department of Contents Software at Sejong University since 2022. His academic journey began with a B.S. from Seoul National University in 2014, followed by a Ph.D. from the same institution in 2020. After completing post-doctoral research at Seoul National University (2020-2022), he joined Sejong University's faculty.

Lee's research centers on the intersection of cryptography and artificial intelligence, with particular expertise in privacy-preserving machine learning through homomorphic encryption techniques. His work focuses on implementing deep learning models on encrypted data without decryption, addressing critical challenges in computational efficiency and accuracy preservation. The fingerprint analysis of his publications reveals strong concentration in Fully Homomorphic Encryption (100%), Approximation Algorithms (97%), and Privacy-Preserving Machine Learning (86%).

His publication trend shows consistent output with 4 papers in 2022 and 2 papers in 2023, primarily appearing in prestigious venues like IEEE Access, IEEE Transactions on Dependable and Secure Computing, and ASIACRYPT. These works demonstrate progressive refinement of techniques for applying homomorphic encryption to neural networks, with particular emphasis on convolutional architectures and efficient polynomial approximations.

Lee's research has garnered significant attention with multiple papers receiving substantial Scopus citations (89 for his PMLR 2022 paper, 47 for his IEEE TDSC 2022 paper), indicating strong impact in the field. His work has also been referenced in 1 patent, suggesting practical applications of his theoretical contributions.