Yeonsu Lee

Ph.D. Student

Affiliation: Department of Statistics, Kyungpook National University (KNU), Daegu 41566, Korea

<Research Interest>

1. Mathematical modeling of infectious diseases
2. Biological statistics
3. Computer Science

Profile

🔎 Profile

Education

• Ph.D. program in Department of Statistics (2025.9 - ) Interdisciplinary Program in AI-Bio Convergence (2026.03– ) Kyungpook National University, Daegu, Korea
• Master’s Program in Department of Statistics (2023.9 - 2025.8) Kyungpook National University, Daegu, Korea
• Bachelor’s Program in Department of Computer Science, Global Software Convergence Major (2020.3 - 2023.8) Interdisciplinary Program in Big Data Major (2022.3 - 2023.8) Kyungpook National University, Daegu, Korea

Experience

• 한국연구재단 석사과정생연구장려금지원사업 연구책임자 (2024.07 - 2025.06)
• IBS BIMAG Winter Intership (2024.1) Institute for Basic Science, Daejeon, Korea
• Student Researcher in Department of Statistics (2022.5 - 2023.8) Kyungpook National University, Daegu, Korea
• Cj올리브네트웍스 X 한국 경제신문 X 퍼브 리모트 인턴쉽 2기 (2022.9 - 2022.12)

Presentation

👩🏻‍🏫 Presentation

Oral presentation

1. Parameter estimation of Influenza in South Korea using the Ensemble Kalman Filter 2025 KDISS Fall meeting, **Kyungpook National University, Daegu, Korea
2. Analyznig influenza trends pre- and post-pandemic using Ensemble Kalman Filtering in epidemicological model 2025 KOSHIS Spring meeting, Korea University, Seoul, Korea
3. Analysis of the impact of COVID-19 variants and vaccination on the time-varying reproduction number: Statistical methods 신,변종 감염병 유행예측과 중재정책 수리모델 플랫폼 개발 워크숍

Poster presentation

1. Development of a Generalized Real-Time Early Detection Model based on Bootstrap Clustering 14th European Conference on Mathematical & Theoretical Biology, Graz, Austria
2. Uncertainty based Real-Time Early Detection Framework for Epidemic Dynamics via Bootstrap Clustering The 15th AIMS Conference, Athens, Greece
3. A Clustering-based Framework for Real-time Early Detection of Seasonal Infectious Disease Outbreaks 2026 Annual Meeting of KSMB, Jeju Island, Korea
4. Developing a Real-Time Early Detection Model using Bootstrap Clustering for various infectious diseases KSIAM 2026 Spring meeting, UNIST, Ulsan, Korea
5. Early Detection of New Outbreaks of Respiratory Viruses using Machine Learning Methods Epidemics 10, Paradise Point, San Diego, USA
6. Influenza Trends in South Korea: Parameter Estimation Before and After the Pandemic with the Ensemble Kalman Filter ACMB-JSMB 2025, Kyoto Terrsa, Kyoto, Japan
7. Developing the Epidemiological Models with Humidity for Influenza cases using Ensemble Kalman Filter methods 2025 YNMS, **Kyungpook National University, Daegu, Korea
8. Exploring Influenza Trends with the impact of Climate Factors in South Korea KSIAM 2024 Annual meeting, BEXCO, Busan, Korea
9. Analysis of sleep patterns in relation to work shifts using nurse sleep data from a wearable device SMB-KSMB 2024, Konkuk University, Seoul, Korea
10. Assessing the impact of the typhoid vaccine using mathematical modeling 2024 KSIAM Spring meeting, Kyungpook National University, Daegu, Korea

Publications

🔖 Publications

RESEARCH PAPERS

<Published>

2026

1. Su Hyun Kim*, Geunsoo Jang*, Yeonsu Lee, Sijin Lee, Huiyoung Hwang, Hyojung Lee, Data-Driven Scheduling Strategies to Minimize Fatigue in Rotating Night-Shift Nurses, Journal of Nursing Mangement, 2026

2025

1. Yeonsu Lee*, Pamela Kim N. Salonga*, Changdae Son, Geunsoo Jang, DaeHyup Koh, Jong-Hoon Kim*, Hyojung Lee*, Effective strategies for typhoid conjugate vaccine delivery: Health and economic insights from the 2015 Kampala outbreak, PLOS Neglected Tropical Disease, 2025

2024

1. Geunsoo Jang*, Jihyeon Kim, Yeonsu Lee, Changdae Son, Kyeong Tae Ko, and Hyojung Lee, Analysis of the impact of COVID-19 variants and vaccination on the time-varying reproduction number: Statistical methods, Frontiers in Public Health, 2024

<Submitted>

1. Yeonsu Lee, Yongin Choi, Jeongsu Lim, and Hyojung Lee, Statistical Framework for Early Warning Detection for Various Infectious Diseases
2. Yoonah Kang, Yeonsu Lee, Changdae Son, Wasim Abbas, Jaehoon Kim, Yongin Choi*, and Hyojung Lee*, Quantifying Variant-Specific Transmissibility and Forecasting Recurrent Summer COVID-19 Outbreaks: An Age-Structured Modeling Study in Korea
3. Jihyeon Kim, Yeonsu Lee, and Hyunju Kim*, Hyojung Lee*, Influenza-Like Illness and Wastewater Surveillance Data Forecasting with Neural Networks and Mathematical Modeling Approaches

Awards

🏆 Awards

1. Best Poster Award (포스터 우수상) 2026 Annual Meeting of KSMB, Jeju Island, Korea
2. Best Poster Award (포스터 우수상) KSIAM 2026 Spring meeting, UNIST, Ulsan, Korea
3. Outstanding Oral Presentation (구연 발표 우수상) 2025 KDISS Fall meeting, **Kyungpook National University, Daegu, Korea
4. Best Research Award (우수 학술상) 2025 KDISS (The Korean Data Information Science Society)
5. Best Poster Award (포스터 최우수상) 2025 YNMS, **Kyungpook National University, Daegu, Korea
6. Best Oral Presentation (구연 발표 대상) ****2025 KOSHIS Spring meeting, Korea University, Seoul, Korea

👩🏻‍💻 Projects

Untitled

👋 Contact

✉️ [email protected] 📱+82 10-3227-3328 🏠 대구광역시 북구