Research
Papers
(Submitted) Estimating the Distribution of Parameters in Differential Equations with Repeated Cross-Sectional Data
(To appear) Hyeontae Jo, Hong Jun Jeon, Junseok Ahn, Saebom Jeon, Jaekyoung Kim, and Seockhoon Chung "Dysfunctional Beliefs and Attitudes about Sleep-6 (DBAS-6): Data-driven Shortened Version from a Machine Learning Approach" Sleep Medicine.
(To appear) Hyeontae Jo, Myna Lim, Hong Jun Jeon, Junseok Ahn, Saebom Jeon, Jaekyoung Kim, Seockhoon Chung "Data-driven Shortened Insomnia Severity Index (ISI): A Machine Learning Approach" Sleep and Breathing
Hyeontae Jo, Hyukpyo Hong, Hyung Ju Hwang, Won Chang, and Jae Kyoung Kim "Density Physics-Informed Neural Network identifies sources of cell heterogeneity in signal transduction under antibiotic stress" Cell Patterns (2024).
Min Sue Park, Hyeontae Jo, Haeun Lee, Se Young Jung, and Hyung Ju Hwang. “Machine Learning-Based COVID-19 Patients Triage Algorithm using Patient-Generated Health Data from Nationwide Multicenter Database” Infectious Diseases and Therapy. (2022)
Se Young Jung, Hyeontae Jo, Hwijae Son, and Hyung Ju Hwang. “Real-World Implications of Rapidly Responsive COVID-19 Spread Model with Time Dependent Parameters Via Deep Learning: Algorithm Development and Validation” Journal of Medical Internet Research. (2020), 22(9):e19907
Rakhoon Hwang, Hyeontae Jo, Kyung Seok Kim, and Hyung Ju Hwang. “The Hybrid Model of a Mathematical Model and Neural Network Model for Rolling Force and Temperature Prediction in Hot Rolling Processes” IEEE Access. (2020), 8: 153123-153133
Hyung Ju Hwang, Jin Woo Jang, Hyeontae Jo, and Jae Young Lee. “Trend to Equilibrium for the Kinetic Fokker-Planck Equation via the Neural Network Approach” Journal of Computational Physics. (2020): 109665
Jaimyun Jung, Jae Ik Yoon, Hyung Keun Park, Hyeontae Jo, and Hyoung Seop Kim, "Microstructure design using machine learning generated low dimensional and continuous design space" Materilia. (2020), 11: 100690
Hyeontae Jo, Hwijae Son, Hyung Ju Hwang, and Eunheui Kim. “Deep Neural Network Approach to Forward-Inverse Problems” Networks and Heterogeneous Media. (2020), 15(2): 247-259
Hyung Ju Hwang and Hyeontae Jo. "The diffusive limit of the Vlasov-Fokker-Planck equation with the chemotactic sensitivity coupled to a parabolic equation" Journal of Mathematical Analysis and Applications 477.2 (2019): 1224-1242
Conferences / Workshop
(Talk) Density Physics-Informed Neural Network: Inferring the Source of Cell-to-Cell Heterogeneity in Intracellular Signaling Dynamics. KSIAM 2023 Annual Meeting
(Talk) 2023 KMS Annual Meeting
(Talk) Density Physics-Informed Neural Network: Inferring the Source of Cell-to-Cell Heterogeneity in Intracellular Signaling Dynamics. ICIAM 2023
(Talk) Density Physics-Informed Neural Network infers an arbitrary density distribution for non-Markovian system. Society for Mathematical Biology Annual Meeting - 2023
(Talk) Density Physics-Informed Neural Network: Inferring Sources of Cell-to-Cell Heterogeneity in Intracellular Signaling Dynamics. 한국수리생물학회
(Talk) Density physics-informed neural network infers an arbitrary density distribution for a non-Markovian system. 2023 KMS Spring Meeting
(Talk) Nonparametric inference methods for intracellular signaling dynamics via deep learning. APCTP 2022 Workshop on Non-equilibrium Phenomena in Physics and Biology
(Talk) Nonparametric inference methods for intracellular signaling dynamics via deep learning. KSIAM 2022 Annual Meeting
(Poster) Nonparametric inference methods in delayed stochastic process. SIAM 2022 Annual Meeting
(Poster) Discovering the inherent dynamics of biological systems via an artificial neural network. 2022 KSIAM Spring Conference
(Talk) COVID19 – Mathematical modeling and machine learning. ReaDiNet2021
(Talk) Endpoint Temperature Prediction model for LD Converters Using Machine-Learning Techniques. 2019 IEEE 6th International Conference on Industrial Engineering and Applications. 2019
Talk & public lecture
2024. 06. 15. (예정)
2024. 06. 14. (예정) 건국대학교
2024. 05. 24. (예정) 포항공과대학교
2024. 03. 21. Physics-informed neural networks: Fitting a mathematical model to real data using artificial neural networks, 고려대학교 공공정책대학
2023. 06. 21. An Inference Method for Arbitrary Density Distributions in Non-Markovian Systems. Pusan National University
2022. 09. 07. Nonparametric inference method in cell signaling dynamics via deep learning. National Institute for Mathematical Sciences
Projects
2021. 03 ~ 2022. 02 크로스 도메인 호환성을 위한 블록체인 플랫폼 및 비즈모델 개발
2020. 11 ~ 2021. 04 산업용 지능형 제어기에서 추출한 데이터를 이용한 인공지능 모델 개발
2020. 11. ~ 2021. 02. (POSCO) Development of a model to improve head/tail thickness deviation of the cold rolling mill
2020. 08. ~ 2020. 10. (ELUON) location tracking algorithm of mobile devices using Mobile Data Terminal
2019. 07. ~ 2020. 02. (POSCO) Development of a temperature prediction model to improve head/tail thickness deviation of the reversing hot rolling mill
2017. 07. ~ 2018. 11. (POSCO) Development of BOF Thermal Composition AI Algorithm at Pohang No.2 Steel Making Plant
IBS seminar presentation
2024. 01. 05. Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery
2023. 10. 19. Machine Learning–Based Automatic Clinical Score Generator and Its Application to Mortality Prediction Using Electronic Health Records
2023. 05. 26. Parameter Estimation of Power Electronic Converters With Physics-Informed Machine Learning
2023. 02. 17. Characterizing possible failure modes in physics-informed neural networks
2022. 11. 11. PI-VAE: Physics-Informed Variational Auto-Encoder for stochastic differential equations
2022. 08. 05. Neural Ordinary Differential Equations
2022. 06. 03. Approximating solutions of the chemical master equation using neural networks
2022. 04. 01. Physics-informed learning of governing equations from scarce data
Awards and News
2024. 01. 03. 기초과학연구원 우수연구원상
2024. 01. 17. Density-PINN 기초과학연구원 Research news, 해외