Introduction

I am an AI researcher at HUINNO, a Seoul-based digital healthcare company providing AI-based diagnostic solutions. Concurrently, I am pursuing my master’s degree at the Data eXperience Laboratory (advised by Prof. Eunil Park) in the Department of Applied Artificial Intelligence, Sungkyunkwan University, Seoul. Previously, I majored in Biotechnology, Bioinformatics, and Big Data Computing at the School of Systems Biomedical Science, Soongsil University, Seoul. I was an undergraduate researcher at the Computational Science and Artificial Intelligence Laboratory (advised by Prof. Kyoungmin Min) in the School of Mechanical Engineering, Soongsil University. My research interests broadly span deep learning, bioinformatics, cheminformatics, drug discovery, materials informatics, graph neural networks, and digital healthcare. For more details, please refer to my Curriculum Vitae.

Core Values in Life

1. Happiness: I believe that love and happiness are life’s highest purposes.
2. Innovation: I am committed to research that enriches human life through science.
3. Impact: I aim to create value through actions that benefit humanity.
4. Integrity: I build the future by facing reality at every turn, without lies or exaggeration.
5. Justice: I pursue choices that are just and reasonable, as well as practical.
6. Passion: I value working hard and finding pleasure in my work.
7. Strength: I strive for physical, intellectual, economic, and aesthetic excellence.
8. Collaboration: I see collaboration as the only way to achieve ambitious goals.
9. Learning: I hold that learning should continue throughout life.
10. Perseverance: I believe that where there is a will, there is a way.

Publications

• “ECG-GraphNet: Advanced Arrhythmia Classification Based on Graph Convolutional Networks”, Myeonghun Lee⁺, Jiwoo Lim⁺, and Jinkook Kim*, Heart Rhythm O2. [Link]

• “Matini-Net: Versatile Material Informatics Research Framework for Feature Engineering and Deep Neural Network Design”, Myeonghun Lee⁺, Taehyun Park⁺, and Kyoungmin Min*, Journal of Chemical Information and Modeling. [Link]

• “Prediction of Protein Aggregation Propensity via Data-driven Approaches”, Seungpyo Kang⁺, Minseon Kim⁺, Jiwon Sun⁺, Myeonghun Lee*, and Kyoungmin Min*, ACS Biomaterials Science & Engineering. [Link]

• “AmorProt: Amino Acid Molecular Fingerprints Repurposing-based Protein Fingerprint”, Myeonghun Lee^+,*, and Kyoungmin Min*, Biochemistry. [Link]

• “AiKPro: Deep Learning Model for Kinome-Wide Bioactivity Profiling Using Structure-based Sequence Alignments and Molecular 3D Conformer Ensemble Descriptors”, Hyejin Park⁺, Sujeong Hong⁺, Myeonghun Lee⁺, Sungil Kang, Rahul Brahma, Kwang-Hwi Cho, and Jae-Min Shin*, Scientific Reports. [Link]

• “Natural Language Processing Techniques for Advancing Materials Discovery: A Short Review”, Joo Hyuk Lee⁺, Myeonghun Lee⁺, and Kyoungmin Min*, International Journal of Precision Engineering and Manufacturing-Green Technology. [Link]

• “Evaluation of Principal Features for Predicting Bulk and Shear Modulus of Inorganic Solids with Machine Learning”, Myeonghun Lee⁺, Minseon Kim, and Kyoungmin Min*, Materials Today Communications. [Link]

• “MGCVAE: Multi-objective Inverse Design via Molecular Graph Conditional Variational Autoencoder”, Myeonghun Lee⁺ and Kyoungmin Min*, Journal of Chemical Information and Modeling. [Link]

• “Novel Solubility Prediction Models: Molecular Fingerprints and Physicochemical Features vs. Graph Convolutional Neural Networks”, Sumin Lee⁺, Myeonghun Lee⁺, Ki-Won Gyak, Sung Dug Kim, Mi-Jeong Kim*, and Kyoungmin Min*, ACS Omega. [Link]

• “A Comparative Study of the Performance for Predicting Biodegradability Classification: The Quantitative Structure−Activity Relationship Model vs the Graph Convolutional Network”, Myeonghun Lee⁺ and Kyoungmin Min*, ACS Omega. [Link]

News

• 2026.09. Patent Registration, “Method and System For Classifying Electrocardiogram Signal”, Jinkook Kim, Myeonghun Lee, Jiwoo Lim, Sunghoon Jung, HUINNO, Korea Intellectual Property Office. [Link]

• 2026.07. Manufacturing Certification (Ministry of Food and Drug Safety), “MEMO CAST” (formerly Vital-PICASO), an AI-based clinical decision support system for predicting the risk of in-hospital cardiac arrest within 24 hours, HUINNO and HUINNO AIM. [Link]

• 2026.06. Clinical trial completed at HUINNO, “Clinical Validity of an AI-Based Biological Signal Analysis Software Vital-PICASO for Predicting the Risk of Hypoxemia within 24hrs Using Vital Sign (SBP, DBP, HR, RR, BT, SpO2) from General Ward Inpatients; A Retrospective, Single-Center, Single-Arm, Superiority-Confirmatory Clinical Trial”.

• 2026.01. Clinical trial completed at HUINNO, “Clinical Validity of an AI-Based Biological Signal Analysis Software Vital-PICASO for Predicting the Risk of Hypotension within 24hrs Using Vital Sign (SBP, DBP, HR, RR, BT, SpO2) from General Ward Inpatients; A Retrospective, Single-Center, Single-Arm, Superiority-Confirmatory Clinical Trial”.

• 2025.11. Clinical trial completed at HUINNO, “Clinical Validity of an AI-Based Biological Signal Analysis Software Vital-PICASO for Predicting the Risk of Cardiac Arrest within 24hrs Using Vital Sign (SBP, DBP, HR, RR, BT, SpO2) from General Ward Inpatients; A Retrospective, Single-Center, Single-Arm, Superiority-Confirmatory Clinical Trial”.

• 2025.05. Accepted, “ECG-GraphNet: Advanced Arrhythmia Classification Based on Graph Convolutional Networks”, Myeonghun Lee⁺, Jiwoo Lim⁺, and Jinkook Kim*, Heart Rhythm O2. [Link]

• 2025.03. Master’s Researcher, Data eXperience Laboratory (Prof. Eunil Park), Department of Applied Artificial Intelligence, Sungkyunkwan University, Seoul, South Korea. [Link]

• 2025.01. Application to and acceptance into the Master’s Program in the Department of Applied Artificial Intelligence at Sungkyunkwan University, Seoul, South Korea. [Link]

• 2024.11. Accepted, “Matini-Net: Versatile Material Informatics Research Framework for Feature Engineering and Deep Neural Network Design”, Myeonghun Lee⁺, Taehyun Park⁺, and Kyoungmin Min*, Journal of Chemical Information and Modeling. [Link]

• 2024.09. HRX 2024, Heart Rhythm Society (Oral), “A Step Forward in Predictive Cardiology: AI-Driven ECG Algorithm for Predicting the Occurrence of Intraventricular Conduction Abnormalities with Wide QRS Complex”, Jinkook Kim*, Myeonghun Lee⁺, Jiwoo Lim⁺, Sunghoon Jung, and Il-Young Oh. [Link]

• 2024.08. Patent application at HUINNO, “Method and System For Predicting Occurrence of Abnormal Waveform in Electrocardiogram”, Myeonghun Lee, Jiwoo Lim, Jinkook Kim, Sunghoon Jung, Korea Patent.

• 2024.08. Submitted, “ECG-GraphNet: Advancing Cardiac Rhythm Analysis through Beat Classification Based on Graph Convolutional Networks”, Myeonghun Lee⁺, Jiwoo Lim⁺, and Jinkook Kim*.

• 2024.06. Submitted, “Matini-Net: Versatile Material Informatics Research Framework for Feature Engineering and Deep Neural Network Design”, Myeonghun Lee⁺, Taehyun Park⁺, and Kyoungmin Min*.

• 2024.04. Patent application at HUINNO, “Method and System For Classifying Electrocardiogram Signal”, Jinkook Kim, Myeonghun Lee, Jiwoo Lim, Sunghoon Jung, Korea Patent.

• 2023.09. Accepted, “Prediction of Protein Aggregation Propensity via Data-driven Approaches”, Seungpyo Kang⁺, Minseon Kim⁺, Jiwon Sun⁺, Myeonghun Lee*, and Kyoungmin Min*, ACS Biomaterials Science & Engineering. [Link]

• 2023.08. Accepted, “AmorProt: Amino Acid Molecular Fingerprints Repurposing-based Protein Fingerprint”, Myeonghun Lee^+,*, and Kyoungmin Min*, Biochemistry. [Link]

• 2023.07. Patent Registration (1025585460000), “An Artificial Intelligence Learning-based Kinase Profiling Device Using Multi-sequence Information of Protein Structure and 3D Structure Descriptor for Predicting Drug Effect and Its Operation Method”, AZothBio, Korea Intellectual Property Office.

• 2023.07. AI Researcher, HUINNO, Seoul, South Korea. [Link]

• 2023.06. Accepted, “AiKPro: Deep Learning Model for Kinome-Wide Bioactivity Profiling Using Structure-based Sequence Alignments and Molecular 3D Conformer Ensemble Descriptors”, Hyejin Park⁺, Sujeong Hong⁺, Myeonghun Lee⁺, Sungil Kang, Rahul Brahma, Kwang-Hwi Cho, and Jae-Min Shin*, Scientific Reports. [Link]

• 2023.05. Accepted, “Natural Language Processing Techniques for Advancing Materials Discovery: A Short Review”, Joo Hyuk Lee⁺, Myeonghun Lee⁺, and Kyoungmin Min*, International Journal of Precision Engineering and Manufacturing-Green Technology. [Link]

• 2023.04. Submitted, “Natural Language Processing Techniques for Advancing Materials Discovery: A Short Review”, Joo Hyuk Lee⁺, Myeonghun Lee⁺, and Kyoungmin Min*.

• 2023.04. Submitted, “Prediction of Protein Aggregation Propensity via Data-driven Approaches”, Seungpyo Kang⁺, Minseon Kim⁺, Jiwon Sun⁺, Myeonghun Lee*, and Kyoungmin Min*. [Link]

• 2023.02. Submitted, “AmorProt: Amino Acid Molecular Fingerprints Repurposing-based Protein Fingerprint”, Myeonghun Lee^+,*, and Kyoungmin Min*. [Link]

• 2023.01. Patent application at AZothBio, “An Artificial Intelligence Learning-based Kinase Profiling Device Using Multi-sequence Information of Protein Structure and 3D Structure Descriptor for Predicting Drug Effect and Its Operation Method”, Jae-Min Shin, Hyejin Park, Sujeong Hong, Sungil Kang, Myeonghun Lee, Korea Patent.

• 2022.11. 2022 Korean Artificial Intelligence Association & NAVER Fall Conference (Poster), “MoReProt: Prediction of Amyloid Sequence Using Molecular Fingerprints Recombination-based Protein Fingerprint”, Myeonghun Lee⁺ and Kyoungmin Min*. [Link]

• 2022.09. 2022 Research Data Analysis Utilization Contest, “Prediction of Isoelectric Point Using Atomic-level Protein Fingerprints”, The Grand Prize (Ministry of Science and ICT’s Award, 과학기술정보통신부 장관상). [Link]

• 2022.08. Accepted, “Evaluation of Principal Features for Predicting Bulk and Shear Modulus of Inorganic Solids with Machine Learning”, Myeonghun Lee⁺, Minseon Kim, and Kyoungmin Min*, Materials Today Communications. [Link]

• 2022.05. Accepted, “MGCVAE: Multi-objective Inverse Design via Molecular Graph Conditional Variational Autoencoder”, Myeonghun Lee⁺ and Kyoungmin Min*, Journal of Chemical Information and Modeling. [Link]

• 2022.03. Accepted, “Novel Solubility Prediction Models: Molecular Fingerprints and Physicochemical Features vs. Graph Convolutional Neural Networks”, Sumin Lee⁺, Myeonghun Lee⁺, Ki-Won Gyak, Sung Dug Kim, Mi-Jeong Kim*, and Kyoungmin Min*, ACS Omega. [Link]

• 2022.03. AI Researcher, AZothBio, Seoul, South Korea. [Link]

• 2022.03. Submitted, “Evaluation of Principal Features for Predicting Bulk and Shear Modulus of Inorganic Solids with Machine Learning”, Myeonghun Lee⁺, Minseon Kim, and Kyoungmin Min*.

• 2022.02. Graduated from the School of Systems Biomedical Science, Soongsil University (Biotechnology, Bioinformatics, Big Data Computing).

• 2022.02. Submitted, “MGCVAE: Multi-objective Inverse Design via Molecular Graph Conditional Variational Autoencoder”, Myeonghun Lee⁺ and Kyoungmin Min*. [Link]

• 2021.12. Accepted, “A Comparative Study of the Performance for Predicting Biodegradability Classification: The Quantitative Structure−Activity Relationship Model vs the Graph Convolutional Network”, Myeonghun Lee⁺ and Kyoungmin Min*, ACS Omega. [Link]

• 2021.12. 2021 Fall International Convention of The Pharmaceutical Society of Korea (Poster), “Multi-class Multi-label Enzyme Function Classification Using Graph Convolutional Network”, Myeonghun Lee⁺ and Kyoungmin Min*.

• 2021.11. 2021 Research Data AI Analysis Utilization Contest, “Singlet-Triplet Energy Gap Prediction Using Graph Convolutional Network”, The Excellence Prize (National Research Council of Science & Technology Chairman’s Award, 국가과학기술연구회 이사장상). [Link]

• 2021.11. 2021 Korea Data Mining Society Fall Conference (Oral), “Enhanced Biodegradability Classification through Graph Convolution Networks”, Myeonghun Lee⁺ and Kyoungmin Min*.

• 2021.11. 2021 Korean Artificial Intelligence Associationㅣ LG AI Research Fall Conference (Poster - Virtual), “Molecular Graph-based Conditional Variable Autoencoder for De Novo Drug Design”, Myeonghun Lee⁺ and Kyoungmin Min*. [Link]

• 2021.11. Submitted, “A Comparative Study of the Performance for Predicting Biodegradability Classification: The Quantitative Structure−Activity Relationship Model vs the Graph Convolutional Network”, Myeonghun Lee⁺ and Kyoungmin Min*.

• 2021.09. Ranked in the top 6% of DACON competition: Samsung AI Challenge for Scientific Discovery.

• 2021.09. ACS Fall 2021 Conference Submission, “Graph Convolutional Network for Organic Solvent and Aqueous Solubility Prediction”, Myeonghun Lee⁺, Sumin Lee, Ki-Won Gyak, Sung Dug Kim, Mi-Jeong Kim*, and Kyoungmin Min*. [Link]

• 2021.09. ACS Fall 2021 Conference Submission, “Solubility Prediction Using Physicochemical Features via Machine Learning”, Sumin Lee⁺, Myeonghun Lee, Ki-Won Gyak, Sung Dug Kim, Mi-Jeong Kim*, and Kyoungmin Min*. [Link]

• 2021.08. ACS Fall 2021 Conference Presentation (Oral - Virtual), “Graph Convolutional Network for Organic Solvent and Aqueous Solubility Prediction”, Myeonghun Lee⁺, Sumin Lee, Ki-Won Gyak, Sung Dug Kim, Mi-Jeong Kim*, and Kyoungmin Min*.

• 2021.08. Submitted, “Novel Solubility Prediction Models: Molecular Fingerprints and Physicochemical Features vs. Graph Convolutional Neural Networks”, Sumin Lee⁺, Myeonghun Lee⁺, Ki-Won Gyak, Sung Dug Kim, Mi-Jeong Kim*, and Kyoungmin Min*. Samsung Advanced Institute of Technology (SAIT) research project.

• 2020.07. Undergraduate Researcher, Computational Science and Artificial Intelligence Laboratory (Prof. Kyoungmin Min, now at Yonsei University), School of Mechanical Engineering, Soongsil University, Seoul, South Korea. [Link]

• 2019.01. Undergraduate Intern, Post-Genome Informatics Laboratory (Prof. Sangsoo Kim), School of Systems Biomedical Science, Soongsil University, Seoul, South Korea. [Link]

• 2016.03. Undergraduate Admission, School of Systems Biomedical Science, Soongsil University, Seoul, South Korea.dergraduate Admission, School of Systems Biomedical Science, Soongsil University, Seoul, South Korea.