
Hyeong Jin Hyun
Asst Professor (F2)
4428D French Hall, West
2815 Commons Way
Cincinnati, Ohio 45219
Email hyunhi@ucmail.uc.edu
Professional Summary
Website: http://hyeongjinhyun.github.io/
Education
Ph.D.: Purdue University 2025 (Statistics)
M.S.: Seoul National University 2020 (Statistics)
B.S.: Seoul National University 2018 (Mathematics)
B.S.: Seoul National University 2018 (Statistics)
Research and Practice Interests
My research lies at the intersection of deep learning and statistical methodology, with a focus on developing principled frameworks that bridge the two fields. I am particularly interested in simulation-based inference, likelihood-free inference, deep generative models, and conformal prediction, as well as their applications in real-world domains such as data privacy, healthcare, and finance.
Positions and Work Experience
2025 -2026 Postdoctoral Researcher, Purdue University,
Publications
Peer Reviewed Publications
Joungyoun Kim, Eun-A Choi, Ye-Eun Han, Jae-woo Lee, Ye-seul Kim, Yonghwan Kim, Hyo-Sun You, Hyeong-Jin Hyun, Hee-Taik Kang. (2020). Association between statin use and all-cause mortality in cancer survivors, based on the Korean health insurance service between 2002 and 2015. Nutrition, Metabolism and Cardiovascular Diseases
Joungyoun Kim, Hyeong-Jin Hyun, Eun-A Choi, Yonghwan Kim, Yoon-Jong Bae, Hee-Taik Kang. (2020). Metformin use reduced the risk of stomach cancer in diabetic patients in Korea: an analysis of Korean NHIS-HEALS database. Gastric Cancer
Hyeong Jin Hyun, Youngrae Kim, Sun Jo Kim, Joungyeon Kim, Johan Lim, Dong Kyu Lim, and Sung Won Kwon. (2021). Constrained principal component analysis with stochastically ordered scores for high-dimensional mass spectrometry data. Chemometrics and Intelligent Laboratory Systems
Hyeong Jin Hyun and Xiao Wang. (2024). Fast Cost-constrained High Dimensional Regression. Statistica Sinica
Hyeong Jin Hyun and Xiao Wang. (2025). Neural Conformal Inference for jump diffusion processes. Journal of Econometrics
Yijia Liu, Hyeong Jin Hyun, and Xiao Wang. (2026). Regularized Physics-Informed Neural Networks for Parameter Estimation in Differential Equation Models. Techonmetrics
Contact Information
Academic - 4428D French Hall, West
2815 Commons Way
Cincinnati
Ohio, 45219
hyunhi@ucmail.uc.edu