Research

Goolgle Scholar

CV

¹(co-)1st author, *(co-)corresponding author

Papers (Ongoing)

• (Under review) G. Hwang, *H. Jo, J.K. Kim, Coupled Oscillator inference, Physical Review X

• (Under review) C. Cho, S. W. Cho, *H. Jo, *H. J. Hwang, "Estimation of System Parameters Including Repeated Cross-Sectional Data: Emulator-Informed Deep-Generative Model" PNAS NEXUS

• (Submitted) H. Cho, *H. Jo, H. J. Hwang, "System inference with Imperfect Data"

• (Submitted) ¹H. Cho, ¹H. Jo, H. J. Hwang, "Prediction for Overall Survival in Multiple Myeloma with XGB-AFT"

• (Submitted) ¹J. Ryu, ¹H. Jo, H.J. Hwang, "Attention with Quantum Fourier Transform for Operator Learning in Dynamical Systems"

• (Submitted) S. Chae, et al., Identifying risk factors of PTSD among a nationwide cohort of firefighters using a machine learning algorithm

• (Preparing - 식생공) 살균제 효율 분석

• (Preparing - 약대/빅데이터) 의약품 평가 지표의 신뢰도 향상을 위한 수학적 필요 조건 분석

• (Preparing) Structure inference of stochastic financial models via deep learning

Papers (Accepted / Published)

2025

• (To appear) ¹H. Jo, K. Joisc, J. K. Kim, Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals, SIAM Journal on Applied Mathematics

• ¹E.S. Lee, ¹H. Jo, H. J. Hwang, "Reverse Engineering for Programmable Logic Controller Structure Estimation via White Box Networks", Journal of Intelligent Manufacturing

• ¹O. R. Cawiding, ¹H. Jo, S. Jeon,  F. R. Ardi, J. K. Kim, S. Chung "Cancer-related Dysfunctional Beliefs and Attitude about Sleep-6 (C-DBAS-6): A practical and accurate shortened version using XGBoost and SymScore", Sleep and Biological Rhythms

• S. Lee , O. R. Cawiding , H. Jo , J. K. Kim , E. Y. Joo "1332 Evaluating Patient Characteristics Influencing the Predictive Accuracy of Sleep Disorder Questionnaires", Sleep

• O. R. Cawiding, S. Lee, H. Jo, S. Kim, S. Suh, E. Y. Joo, S. Chung, J. K. Kim, "SymScore: Machine Learning Accuracy Meets Transparency in a Symbolic Regression-Based Clinical Score Generator" Computers in Biology and Medicine

2024

• ¹H. Jo, ¹S. W. Cho, H. J. Hwang, "Estimating the Distribution of Parameters in Differential Equations with Repeated Cross-Sectional Data", PLOS Computational Biology

• ¹H. Jo, H. J. Jeon, J. Ahn, S. Jeon,  J. K. Kim, S. Chung "Dysfunctional Beliefs and Attitudes about Sleep-6 (DBAS-6): Data-driven Shortened Version from a Machine Learning Approach" Sleep Medicine

• ¹H. Jo, ¹M. Lim, H. J. Jeon, J. Ahn, S. Jeon, J. K. Kim, S. Chung "Data-driven Shortened Insomnia Severity Index (ISI): A Machine Learning Approach" Sleep and Breathing

• ¹H. Jo, ¹H. Hong, H. J. Hwang, W. Chang,  J. K. Kim  "Density Physics-Informed Neural Network identifies sources of cell heterogeneity in signal transduction under antibiotic stress" Cell Patterns

2022

• ¹M. S. Park, ¹H. Jo, H. Lee, S. Y. Jung, H. J. Hwang. "Machine Learning-Based COVID-19 Patients Triage Algorithm using Patient-Generated Health Data from Nationwide Multicenter Database" Infectious Diseases and Therapy

2020

• ¹S. Y. Jung, ¹H. Jo, H. Son, H. J. 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

• R. Hwang, H. Jo, K. S. Kim, H. J. Hwang. “The Hybrid Model of a Mathematical Model and Neural Network Model for Rolling Force and Temperature Prediction in Hot Rolling Processes” IEEE Access

• H. J. Hwang, J. W. Jang, ¹H. Jo, J. Y. Lee. “Trend to Equilibrium for the Kinetic Fokker-Planck Equation via the Neural Network Approach” Journal of Computational Physics

• J. Jung, J. I. Yoon, H. K. Park, H. Jo, H. S. Kim, "Microstructure design using machine learning generated low dimensional and continuous design space" Materialia

• ¹H. Jo, ¹H. Son, H. J. Hwang, E. Kim. "Deep Neural Network Approach to Forward-Inverse Problems" Networks and Heterogeneous Media

2019

• H. J. Hwang, ¹H. 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

Conferences / Workshop

• (Talk) SIAM Annual Meeting (Montreal, Canada; July 27- August 01, 2025)

• (Invited lecture) International Workshop on Computational and Mathematical Methods in Data Science (Philippine; April 3–5, 2025)

• (Talk)KSIAM 2024 Annual Meeting

• (Talk) Estimating the Distribution of Parameters in Differential Equations with Repeated Cross-Sectional Data, 2024 KMS Annual Meeting

• (Talk) Density physics-informed neural networks reveal sources of cell heterogeneity in signal transduction,  SMB 2024

• (Talk) Density Physics-Informed Neural Network: Inferring Sources of Cell-to-Cell Heterogeneity in Intracellular Signaling Dynamics, 2024 KSIAM Spring Conference

• (Talk) Density Physics-Informed Neural Network infers an arbitrary density distribution for non-Markovian system, 2024 KMS Spring Meeting

• (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 SMB

• (Talk) Density Physics-Informed Neural Network: Inferring Sources of Cell-to-Cell Heterogeneity in Intracellular Signaling Dynamics. KSMB 2023

• (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) COVID-19 – 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.

Talk & public lecture

• 2025. 08. 19 바이오⋅의료데이터를 위한 수학, 고려대학교 지역혁신 선도연구센터 (바이오헬스)

• 2025. 08. 14 데이터 사이언스를 위한 수학, 부산대학교 데이터사이언스 대학원

• 2025. 02. 03 설문지 간소화: 통계기법부터 머신러닝까지. 서울아산병원

• 2025. 01. 06 Invited lecture. U. Birmingham (UK)

• 2024. 07. 10 Physics-informed neural networks: Fitting a mathematical model to real data using artificial neural networks. Korea Institute for Advanced Study (KIAS)

• 2024. 06. 15. 인공지능이 수학에 어떻게 쓰일까요? 광양고등학교

• 2024. 06. 14.  Physics-informed neural networks: Fitting a mathematical model to real data using artificial neural networks. 건국대학교

• 2024. 05. 24. Physics-informed neural networks: Fitting a mathematical model to real data using artificial neural networks. 포항공과대학교

• 2024. 03. 21. Physics-informed neural networks: Fitting a mathematical model to real data using artificial neural networks. 고려대학교

• 2023. 06. 21. An Inference Method for Arbitrary Density Distributions in Non-Markovian Systems. 부산대학교

• 2022. 09. 07. Nonparametric inference method in cell signaling dynamics via deep learning. 국가수리과학연구소

Projects

산학연 교류 이력

• 2021. 03 ~ 2022. 02 (국내기업체) 크로스 도메인 호환성을 위한 블록체인 플랫폼 및 비즈모델 개발

• 2020. 11 ~ 2021. 04 (국내기업체) 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

국내 병원 교류 이력

• 분당서울대학교병원 (가정의학과 정세영 교수님): COVID-19 자가 보고 데이터를 활용한 감염병 중증환자 병상 관리 문제를 수행

• 서울아산병원 (정신건강의학과 정석훈 교수님): 머신러닝과 통계기법을 이용한 불면증 관리 도구 개선을 통하여 신속한 수면 진단 문제 해결을 수행

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. 10. 07. KUS New Challenger 

• 2024. 01. 03. 기초과학연구원 우수연구원상

• 2024. 01. 17. Density-PINN 기초과학연구원 Research news (연합뉴스), 해외보도자료