Jooyoung Jeon (전주영)
Research Interests
I am an Associate Professor at the Graduate School of Future Strategy, KAIST, Korea. I am interested in developing new forecasting models and quantifying relevant uncertainties. I have mainly concerned the following application areas: probabilistic or hierarchical forecast modelling for energy (e.g. wind power, wave energy, PV and smart meters), the environment (e.g. air pollution, temperature and irradiation) and financial market risk modelling.
Education
2006 –2010 Saïd Business School, University of Oxford, UK
DPhil in Management Studies (concentration on Management Science)
2005 –2006 London Business School, UK
MSc in Finance
1994 –1998 Seoul National University, Seoul, Korea
BSc in Computer Science and Statistics
Positions Held
2019 – Present Associate Professor, Graduate School of Future Strategy (미래전략대학원), KAIST (Korea Advanced Institute of Science and Technology), Korea
2013 – 2019 Assistant Professor, School of Management, University of Bath, UK
2016 – 2018 Visiting Associate Professor, Graduate School of Engineering Practice, Seoul National University, Korea
2012 – 2013 Assistant Professor, Department of Management Science, Strathclyde Business School, University of Strathclyde, UK
2010 – 2012 Her Majesty’s Government Junior Research Fellow, Smith School of Enterprise and the Environment, University of Oxford, UK
2001 – 2005 Co-Founder and Principle Consultant, DFocus Data Warehouse Consulting, Korea
2000 – 2001 IT Consultant in Data Mining and SAP Business Information Warehouse, IBM, Korea
1998 – 2000 IT Consultant (alternative military service), G&Tech, Korea
Publications
J Park, E Alvatenga, J Jeon, R Li, F Petropoulos, H Kim and K Ahn. (2024) Probabilistic Forecast-based Portfolio Optimization of Electricity Demand at Low Aggregation Levels. Applied Energy, 353, 122109.
H Kim, S Park, M Jeong, H Byun, J Kim, Dy Lee, J Jeon, E Yi, K Ahn. (2023) Scaling behavior and text cohesion in Korean texts, Plos One, 18(8).
H Kim, E Yi, J Jeon, T Park, K Ahn. (2023) After the Split: Market Efficiency of Bitcoin Cash, Computational Economics, 1-17.
Petropoulos, F., Apiletti, D., Assimakopoulos, V., ... Jeon, Jooyoung, …, Ziel. (2022) Forecasting: theory and practice. International Journal of Forecasting, in press. DOI: 10.1016/j.ijforecast.2021.11.001. IJF ISSN 0169-2070: JCR 91%; Impact Factor 2.825,
Erick Meira., Cyrino Oliveira, F. L. and Jeon, J. (2021) Treating and Pruning: new approaches to forecasting model selection and combination using prediction intervals. International Journal of Forecasting, 37, 547-568, DOI: 10.1016/j.ijforecast.2020.07.005 . IJF ISSN 0169-2070: JCR 91%; Impact Factor 2.825
Jeon, J., Panagiotelis, A. and Petropoulos, F. (2019) Probabilistic forecast reconciliation with applications to wind power and electric load. European Journal of Operational Research, 279, 364-379. EJOR ISSN 0377-2217: JCR 97%; Impact Factor 4.213
Taylor, J.W and Jeon, J. (2018) Probabilistic Forecasting of Wave Height for Offshore Wind Turbine Maintenance. European Journal of Operational Research, 267, 877-890. EJOR ISSN 0377-2217: JCR 97%; Impact Factor 4.213
Jeon, J. and Taylor, J.W. (2016) Short-term Density Forecasting of Wave Energy Using ARMA-GARCH models and Kernel Density Estimation. International Journal of Forecasting, 32, 991-1004. IJF ISSN 0169-2070: JCR 91%; Impact Factor 2.825
Taylor, J.W. and Jeon, J. (2015) Forecasting wind power quantiles using conditional kernel estimation. Renewable Energy, 80, 370-379. RE ISSN 0960-1481: JCR 90%; Impact Factor 6.274
Jeon, J. and Taylor, J.W. (2013) Using CAViaR Models with Implied Volatility for Value at Risk Estimation. Journal of Forecasting, 32, 62-71. JoF ISSN 0277-6693: JCR 67%; Impact Factor 1.570
Jeon, J. and Taylor, J.W. (2012) Using Conditional Kernel Density Estimation for Wind Power Density Forecasting. Journal of the American Statistical Association, 107, 66-79. JASA ISSN 0162-1459: JCR 95%; Impact Factor 3.989
Research Projects
AI 기반 2차시장 의류 가치평가모형 개발연구 (차란-마인이즈)
풍력발전량 예측 기반 VPP 플랫폼 서비스 (중소벤처기업부, 브이피피랩)
외부 경제 데이터를 통한 생명보험 시장 예측 (교보생명,디플래닉스)
계량모형 활용 등을 통한 관세청 조기경보시스템 고도화방안 연구 (관세청)
AI를 활용한 안구건조증 진단 (삼성의료원)
Students
PhD Program (박사) 졸업 3명, 재학 9명
MSc Program (석사) 졸업 12명, 재학 13명