Dr. Hoyeon Jeong, Yonsei University, South Korea
Hoyeon Jeong is a Postdoctoral Researcher at the Medical Research Institute, Sungkyunkwan University, specializing in bioinformatics and digital healthcare. With a Ph.D. in Biostatistics from Yonsei University Wonju College of Medicine, Dr. Jeong developed an advanced neoantigen prediction model using graph neural networks, demonstrating significant accuracy and clinical relevance. His research spans deep learning, network science, and bioinformatics, focusing on spatial transcriptomics, protein-protein interactions, and digital biomarkers. Dr. Jeong has previously worked as a Senior Researcher at Gangwon Research Institute of ICT Convergence and as a Deputy at the HPC Research Center and MEIS development team, contributing to big data analytics, medical data analysis, and system engineering. His academic background includes an M.S. in Physics from Sungkyunkwan University and a B.S. in Physics from Kangwon National University.
Professional Profile:
ORCID
Summary of Suitability for Best Researcher Award:
Dr. Hoyeon Jeong is an outstanding candidate for the Best Researcher Award, based on his significant contributions and accomplishments in the fields of deep learning, bioinformatics, and digital healthcare. His extensive research background, innovative projects, and leadership roles underscore his suitability for this prestigious recognition.
Education:
- Ph.D. in Biostatistics
- Institution: Yonsei University Wonju College of Medicine, Wonju-si, Gangwon-do, Republic of Korea
- Dates: September 2019 – February 2023
- Dissertation: Development of a neoantigen prediction model using graph neural network
- Advisor: Dae Ryong Kang
- Key Research Areas: Applied graph neural networks for neoantigen prediction, protein-protein interaction (PPI) network analysis, cardiovascular disease prediction using NHIS data, digital biomarkers research, and indoor air quality analysis.
- M.S. in Physics
- Institution: Sungkyunkwan University, Suwon, Gyeonggi-do, Republic of Korea
- Dates: March 2007 – February 2009
- Thesis: Feasibility Study of Muons in Fast Simulation at the CMS Experiment
- Advisor: Young-Il Choi
- Key Research Areas: Feasibility of Monte Carlo simulations for Higgs boson detection at CERN.
- B.S. in Physics
- Institution: Kangwon National University, Chuncheon-si, Gangwon-do, Republic of Korea
- Dates: March 1999 – February 2006
- Thesis: Neutron Scattering from Nucleus
- Advisor: Moon Hoe Cha
- Key Research Areas: Simulation of neutron scattering theory using computational physics.
Work Experience:
- Postdoctoral Researcher
- Institution: Medical Research Institute, Sungkyunkwan University, Seoul, Republic of Korea
- Dates: March 2023 – Present
- Main Responsibilities: Bioinformatician focusing on spatial transcriptomics for tumor microenvironment analysis; Project manager for pathology image search using foundation models.
- Senior Researcher, Team Leader
- Institution: Gangwon Research Institute of ICT Convergence, Gangneung-Wonju National University, Wonju-si, Gangwon-do, Republic of Korea
- Dates: May 2017 – May 2019
- Main Responsibilities: Developed a big data analytics platform; Architected deep learning models for medical data analysis.
- Deputy
- Institution: HPC Research Center, Moasys Corporation, Seoul, Republic of Korea
- Dates: July – November 2014
- Main Responsibilities: Supported users of the Tachyon II supercomputer at KISTI; Provided solutions for Unix-like systems migration.
Publication top Notes:
Development and Validation of a Real-Time Service Model for Noise Removal and Arrhythmia Classification Using Electrocardiogram Signals
GraphMHC: Neoantigen prediction model applying the graph neural network to molecular structure
Comparison of Newly Proposed LDL-Cholesterol Estimation Equations
GraphMHC: neoantigen prediction model applying the graph neural network to molecular structure
Evaluation of an air quality warning system for vulnerable and susceptible individuals in South Korea: an interrupted time series analysis.