Hyeong Jun Lee
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Hyeong Jun Lee, portrait.

Hyeong Jun Lee

I work across computational hemodynamics, physics-informed AI, wearable biosignals and medical devices.

Postdoctoral Researcher, Multiscale Fluid Dynamics Lab, School of Mechanical Engineering, Yonsei University

Project Researcher, Yonsei University Health System, 4D CT-FFR project

Education

  1. Mar. 2020 – Aug. 2026

    Ph.D. in Mechanical Engineering (Integrated M.S.–Ph.D. Program) Yonsei University, Seoul, Republic of Korea

    Dissertation: "Patient-Specific Computational Hemodynamics: Flow Field Analysis for Cardiovascular Assessment"; Advisor: Prof. Joon Sang Lee

  2. Mar. 2016 – Feb. 2020

    B.Eng. in Mechanical Engineering Pusan National University, Busan, Republic of Korea

Appointments

  1. Sep. 2026 – Present

    Postdoctoral Researcher, Multiscale Fluid Dynamics Lab (PI: Prof. Joon Sang Lee) Yonsei University, Seoul, Republic of Korea

    Appointment: Technical Research Personnel (alternative military service, through Aug. 2027), Engineering Research Institute, Yonsei University

  2. Mar. 2020 – Aug. 2026

    Graduate Research Assistant, Multiscale Fluid Dynamics Lab (Advisor: Prof. Joon Sang Lee) Yonsei University, Seoul, Republic of Korea

  3. Jan. 2021 – Jun. 2021

    Research Intern E8 (E8IGHT Co., Ltd.), Seoul, Republic of Korea

Publications

4 journal articles · 2 proceedings · 1 under revision · † first author · * corresponding author

Journal articles (SCIE)

  1. Synthesis of coronary 4D CT image by denoising diffusion probabilistic model

    T.H. Han†, Y.W. Kim, H.J. Lee, J.S. Kim, S.G. Lee, D.H. Yang, H.M. Oh, D.S. Kim, S.Y. Shin, S. Song, J.S. Lee*

    Computer Methods and Programs in Biomedicine · 282, 109382 · 2026 Co-author doi:10.1016/j.cmpb.2026.109382
    BibTeX 
    @article{Han2026j1,
  author = {Han, T. H. and Kim, Y. W. and Lee, H. J. and Kim, J. S. and Lee, S. G. and Yang, D. H. and Oh, H. M. and Kim, D. S. and Shin, S. Y. and Song, S. and Lee, J. S.},
  title = {{Synthesis of coronary 4D CT image by denoising diffusion probabilistic model}},
  journal = {Computer Methods and Programs in Biomedicine},
  volume = {282},
  pages = {109382},
  year = {2026},
  doi = {10.1016/j.cmpb.2026.109382}
}

  2. A Physics-Integrated Deep Learning Approach for Patient-Specific Non-Newtonian Blood Viscosity Assessment using PPG

    H.J. Lee†, Y.W. Kim, S.Y. Shin, S.L. Lee, C.H. Kim, K.S. Chung*, J.S. Lee*

    Computer Methods and Programs in Biomedicine · 265, 108740 · 2025 First author doi:10.1016/j.cmpb.2025.108740
    BibTeX 
    @article{Lee2025j2,
  author = {Lee, H. J. and Kim, Y. W. and Shin, S. Y. and Lee, S. L. and Kim, C. H. and Chung, K. S. and Lee, J. S.},
  title = {{A Physics-Integrated Deep Learning Approach for Patient-Specific Non-Newtonian Blood Viscosity Assessment using PPG}},
  journal = {Computer Methods and Programs in Biomedicine},
  volume = {265},
  pages = {108740},
  year = {2025},
  doi = {10.1016/j.cmpb.2025.108740}
}

  3. Optimization of tricuspid membrane mechanism for effectiveness and leaflet longevity through hemodynamic analysis

    Y.W. Kim†, H.J. Lee, S.J. Jung, J.H. Kim*, J.S. Lee*

    Engineering Applications of Computational Fluid Mechanics · 16(1), 1587–1600 · 2022 Co-author doi:10.1080/19942060.2022.2104929
    BibTeX 
    @article{Kim2022j3,
  author = {Kim, Y. W. and Lee, H. J. and Jung, S. J. and Kim, J. H. and Lee, J. S.},
  title = {{Optimization of tricuspid membrane mechanism for effectiveness and leaflet longevity through hemodynamic analysis}},
  journal = {Engineering Applications of Computational Fluid Mechanics},
  volume = {16},
  number = {1},
  pages = {1587--1600},
  year = {2022},
  doi = {10.1080/19942060.2022.2104929}
}

  4. Optimization of FFR prediction algorithm for gray zone by hemodynamic features with synthetic model and biometric data

    H.J. Lee†, Y.W. Kim†, J.H. Kim, Y.J. Lee, J.S. Moon, P. Jeong, J.H. Jeong, J.S. Kim*, J.S. Lee*

    Computer Methods and Programs in Biomedicine · 220, 106827 · 2022 Co-first author doi:10.1016/j.cmpb.2022.106827
    BibTeX 
    @article{Lee2022j4,
  author = {Lee, H. J. and Kim, Y. W. and Kim, J. H. and Lee, Y. J. and Moon, J. S. and Jeong, P. and Jeong, J. H. and Kim, J. S. and Lee, J. S.},
  title = {{Optimization of FFR prediction algorithm for gray zone by hemodynamic features with synthetic model and biometric data}},
  journal = {Computer Methods and Programs in Biomedicine},
  volume = {220},
  pages = {106827},
  year = {2022},
  doi = {10.1016/j.cmpb.2022.106827}
}

Peer-reviewed proceedings

  1. Patient-Specific Coronary Flow Field Prediction Using Physics-Informed Neural Operators

    H.J. Lee†, T.H. Han, J.S. Kim, S.G. Lee, J.S. Lee*

    Proc. ASME 2026 Design of Medical Devices Conference (DMD2026) · V001T02A010 · 2026 First author doi:10.1115/DMD2026-1091 figure
    BibTeX 
    @inproceedings{Lee2026c1,
  author = {Lee, H. J. and Han, T. H. and Kim, J. S. and Lee, S. G. and Lee, J. S.},
  title = {{Patient-Specific Coronary Flow Field Prediction Using Physics-Informed Neural Operators}},
  booktitle = {Proc. ASME 2026 Design of Medical Devices Conference (DMD2026)},
  address = {Minneapolis, MN, USA},
  pages = {V001T02A010},
  year = {2026},
  doi = {10.1115/DMD2026-1091}
}

  2. Deriving Dynamic Fractional Flow Reserve From 4D Coronary CT Synthesized by a Diffusion Model

    T.H. Han†, Y.W. Kim, H.J. Lee, J.S. Kim, S.G. Lee, D.H. Yang, H.M. Oh, J.S. Lee*

    Proc. ASME 2026 Design of Medical Devices Conference (DMD2026) · V001T02A011 · 2026 Co-author doi:10.1115/DMD2026-1092
    BibTeX 
    @inproceedings{Han2026c2,
  author = {Han, T. H. and Kim, Y. W. and Lee, H. J. and Kim, J. S. and Lee, S. G. and Yang, D. H. and Oh, H. M. and Lee, J. S.},
  title = {{Deriving Dynamic Fractional Flow Reserve From 4D Coronary CT Synthesized by a Diffusion Model}},
  booktitle = {Proc. ASME 2026 Design of Medical Devices Conference (DMD2026)},
  address = {Minneapolis, MN, USA},
  pages = {V001T02A011},
  year = {2026},
  doi = {10.1115/DMD2026-1092}
}

Manuscript under revision

  1. Multi-Model Deep-Learning Ensemble for Predicting 24-Hour Fluid Bolus Administration from Continuous Photoplethysmography Spectrogram Analysis

    H.J. Lee†, J. Myung, J.Y. Hong*, J.S. Lee*

    Engineering Applications of Artificial Intelligence · First revision under review First author
    BibTeX 
    @unpublished{Leem1,
  author = {Lee, H. J. and Myung, J. and Hong, J. Y. and Lee, J. S.},
  title = {{Multi-Model Deep-Learning Ensemble for Predicting 24-Hour Fluid Bolus Administration from Continuous Photoplethysmography Spectrogram Analysis}},
  note = {First revision under review, Engineering Applications of Artificial Intelligence}
}

Talks

16 talks · 6 international · 10 domestic · 9 presented by me

International

  1. 2026

    Patient-Specific Coronary Flow Field Prediction Using Physics-Informed Neural Operators

    DMD2026 Poster · presented
  2. 2026

    Dynamic Fractional Flow Reserve from 4D Coronary CT Synthesized by a Diffusion Model T.H. Han et al. (incl. H.J. Lee)

    DMD2026 Poster · co-author
  3. 2025

    Patient-Specific Coronary Flow Field Prediction Using Physics-Informed Neural Operators

    ACFM Oral · presented
  4. 2024

    AI-based Hemorheology Prediction with Patient-Specific Biometric Boundary Conditions

    ICTAM Short oral & poster · presented
  5. 2022

    Optimization of Artificial Intelligence Algorithms for FFR Prediction in Gray Zone H.J. Lee, J.S. Lee

    ICMTE Oral · presented
  6. 2021

    Estimating CFD-based CT FFR using lattice Boltzmann method – 3D geometry auto segmentation and novel patient-specific computation

    ESCHM-ISCH-ISB Oral · presented

Domestic

  1. 2025

    A Physics-Integrated Deep Learning Approach for Patient-Specific Non-Newtonian Blood Viscosity Assessment using PPG

    BESCO Poster · presented
  2. 2025

    Time-resolved Coronary Flow Visualization from Single-phase CT T.H. Han et al. (incl. H.J. Lee)

    BESCO Poster · co-author
  3. 2024

    Arterial Blood Pressure and Blood Viscosity Estimation from AI-based PPG Analysis D.Y. Lee et al. (incl. H.J. Lee)

    BESCO Poster · co-author
  4. 2024

    FFR Prediction with Quantum Machine Learning: Accurate and Non-invasive Diagnosis with Limited Features S.W. Kwon et al. (incl. H.J. Lee)

    BESCO Poster · co-author
  5. 2024

    Blood viscosity estimation from wearable device using AI-based PPG analysis D.Y. Lee et al. (incl. H.J. Lee)

    BESCO Poster · co-author
  6. 2024

    Carved membrane design for tricuspid valve regurgitation treatment S.E. Kim et al. (incl. H.J. Lee)

    BESCO Poster · co-author
  7. 2023

    Unlocking Predictive Health Outcomes with Biometric Data H.J. Lee, J.S. Lee

    KSME Oral · presented
  8. 2023

    Modeling Coronary Artery Hemodynamics: Exploring DCNN Surrogate Models in Preliminary Research

    BESCO Oral · presented
  9. 2022

    Artificial Intelligence Algorithms for FFR Prediction in Gray Zone by Single-view Angiography

    BESCO Short oral & poster; Best Paper Award · presented
  10. 2021

    Autonomous Cardiovascular Hemodynamics Analysis using Patient-Specific CFD Simulation with Unsupervised Learning-based Coronary Artery Segmentation J.H. Kim et al. (incl. H.J. Lee)

    BESCO Oral · co-author

Patents

16 filings · 2 registered · 14 pending

  1. P1

    AI-based noninvasive urodynamics test method and apparatus

    Registered No. 10-2902500, Dec. 2025 KR 10-2022-0085583

  2. P2

    Optimization system and method of AI algorithm for prediction coronary artery lesions based on FFR

    Registered No. 10-2882193, Nov. 2025 KR 10-2022-0030019

  3. P3

    Patient-specific coronary flow prediction method based on physics-informed neural operators

    pending, filed 2026 KR 10-2026-0003225

  4. P4

    Deep learning-based multiphase coronary CT interpolation system and method

    pending, filed 2025 US 19/397,163

  5. P5

    Deep learning-based multiphase coronary CT interpolation system and method

    pending, filed 2025 KR 10-2025-0149607

  6. P6

    Device and method for predicting viscosity using AI in a viscosity prediction system

    pending, filed 2025 PCT/KR2025/002462

  7. P7

    Device and method for predicting viscosity using AI in a viscosity prediction system

    pending, filed 2025 KR 10-2025-0021284

  8. P8

    Deep learning-based multiphase coronary CT interpolation method

    pending, filed 2024 KR 10-2024-0168733

  9. P9

    Method for predicting blood glucose and diabetes using PPG signals and biometric information

    pending, filed 2024 KR 10-2024-0147541

  10. P10

    Wearable device for monitoring glaucoma suspect and method for monitoring glaucoma suspect

    pending, filed 2024 PCT/KR2024/012365

  11. P11

    Non-Newtonian fluid viscosity modeling of patient blood using wearable device-based PPG and biometric information

    pending, filed 2024 KR 10-2024-0026709

  12. P12

    Systolic and diastolic viscosity prediction algorithm using wearable device-based PPG and biometric information

    pending, filed 2024 KR 10-2024-0028201

  13. P13

    Glucose and diabetes prediction algorithm using wearable device-based PPG and biometric information

    pending, filed 2023 KR 10-2023-0144347

  14. P14

    Wearable device for monitoring glaucoma suspect and method for monitoring glaucoma suspect

    pending, filed 2023 KR 10-2023-0118582

  15. P15

    Glaucoma diagnosis method and system based on contactless biosignals

    pending, filed 2023 KR 10-2023-0078883

  16. P16

    Optimization system and method of AI algorithm for prediction coronary artery lesions based on FFR

    pending, filed 2022 US 17/820,819

Funded projects (participating researcher)

  1. Jun. 2022 – Feb. 2029

    Real-Time Precision Medicine Platform Based on Smart Hemodynamic Indices

    National Research Foundation of Korea (NRF), Leading Research Center Program NRF-2022R1A5A1022977

  2. Apr. 2024 – Dec. 2026

    4D Coronary Flow Visualization from CT in Real Time (4D CT-FFR)

    Ministry of Health and Welfare / KHIDI, Clinical-Needs Translational Research RS-2024-00406717

  3. Apr. 2025 – Dec. 2028

    4D Flow-Based Diagnostic Device for Dynamic Risk Assessment of Anomalous Origin of the Coronary Artery in Children and Adolescents

    Ministry of Health and Welfare / KHIDI, Pediatric Disease R&D Program RS-2025-02263580

  4. Jul. 2024 – Jun. 2026

    Patient-Specific Coronary Artery Disease Risk Analysis Software

    Ministry of SMEs and Startups, Startup Growth Technology Development Program (TIPS) RS-2024-00441761

  5. Sep. 2020 – Dec. 2025

    Patient-Specific Implantable Device for Tricuspid Regurgitation Using 3D Heart Printing and 4D-CFD Simulation

    Ministry of Health and Welfare / Korea Medical Device Development Fund KMDF_PR_20200901_0104

  6. Apr. 2022 – Dec. 2024

    Variable Negative-Pressure Tunnel for Respiratory Infection Control

    Ministry of Health and Welfare / KHIDI, Infectious Disease Medical Safety Technology Program HG22C0001

  7. Feb. 2020 – May 2022

    High-Speed Point-of-Care FFR Simulator for Cardiovascular Diagnosis and Treatment

    NRF, Bio & Medical Technology Development Program 2017M3A9E907337122

Awards and fellowships

  1. 2026

    Merit Academic Paper Award School of Mechanical Engineering, Yonsei University, for the 2025 CMPB paper on PPG-based non-Newtonian blood viscosity assessment (J2)

  2. 2022

    Best Paper Award Biomedical Engineering Society for Circulation (BESCO)

  3. 2022

    Merit Academic Paper Award Yonsei University

  4. 2022

    Best Paper Award School of Mechanical Engineering, Yonsei University

  5. 2022–2025

    BK21 FOUR Graduate Research Scholarship (7 semesters) Fellowship, Ministry of Education / NRF

  6. 2020–2021

    BK21 PLUS Scholarship Fellowship, Ministry of Education / NRF

  7. 2021

    Academic Research Fellowship (ARF) Fellowship, Yonsei University

Teaching

  1. Mar. 2020 – Dec. 2020

    Teaching Assistant School of Mechanical Engineering, Yonsei University

Skills

Computational
image-based, patient-specific coronary CFD; lattice Boltzmann method; hemodynamic indices (FFR, wall shear stress); non-Newtonian blood rheology
Machine learning
physics-informed neural networks and neural operators (DeepONet/PINO); surrogate modeling; diffusion models; CNN/LSTM; ensemble learning
Data
coronary CT angiography (incl. 4D CT); invasive FFR; smartwatch PPG signals; multi-institutional clinical collaborations
Languages
Korean (native); English (professional working proficiency)