‪Seung-Hyun Victor Oh‬ - ‪Google Scholar‬

Get my own profile

Cited by

	All	Since 2019
Citations	16	16
h-index	2	2
i10-index	1	1

0

8

4

2022202320242 7 7

Co-authors

Woohyun HwangPostdoctoral Research Fellow, Yonsei UniversityVerified email at yonsei.ac.kr
Kwangrae KimUniversity of Texas at AustinVerified email at utexas.edu
Ji-Hwan LeeYonsei UniversityVerified email at yonsei.ac.kr
Giyeok LeeDepartment of Materials Science and Engineering, Yonsei UniversityVerified email at yonsei.ac.kr

Seung-Hyun Victor Oh

Seung-Hyun Victor Oh

YONSEI University , Seoul, Korea

Verified email at yonsei.ac.kr

Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Using Feature‐Assisted Machine Learning Algorithms to Boost Polarity in Lead‐Free Multicomponent Niobate Alloys for High‐Performance Ferroelectrics SHV Oh, W Hwang, K Kim, JH Lee, A Soon Advanced Science 9 (13), 2104569, 2022	13	2022
Exploring anharmonic lattice dynamics and dielectric relations in niobate perovskites from first-principles self-consistent phonon calculations K Kim, W Hwang, SHV Oh, A Soon npj Computational Materials 9 (1), 154, 2023	3	2023
Recalibrating the Experimentally Derived Structure of the Metastable Surface Oxide on Copper via Machine Learning-Accelerated In Silico Global Optimization HJ Kim, G Lee, SHV Oh, C Stampfl, A Soon ACS nano, 2024		2024
Insights into Enhanced Antiferroelectricity in Doped-Niobate Perovskites for High Energy-Storage Density Applications Through Data-Informed In-Silico Experiments W Hwang, K Kim, SH Oh, A Soon Available at SSRN 4712614, 0

The system can't perform the operation now. Try again later.

Articles 1–4