information
Rial Arifin Rajagukguk, PhD
As a researcher, I specialize in a range of advanced fields including computer vision, machine learning, deep learning, remote sensing, electric vehicles, satellite technology, sky cameras, and solar energy. My work focuses on the intersection of these disciplines to drive innovation and practical applications. One of my significant projects involved the development of a sophisticated model to predict solar irradiance. This model utilizes a combination of data from sky cameras and satellites to provide accurate and real-time predictions. The primary application of this model is for electric vehicles in motion, allowing them to optimize their energy consumption based on predicted solar energy availability. By integrating these diverse technologies, the model enhances the efficiency and sustainability of electric vehicles, contributing to the broader goals of reducing carbon emissions and promoting renewable energy sources.
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Educations
• PhD, Kookmin University, South Korea (2021 - 2024) “ Solar Radiation Prediction Based on the Images of Satellite and Sky Camera for the Energy Management of Electric Vehicles “
• MSc, Kookmin University, South Korea (2019 - 2021) “ Solar Irradiance Forecasting using Sky Images “
• BSc, Institut Teknologi Bandung, Indonesia (2012 - 2017) “ Parametric Study of Cooling Film and Implementation on One Axial Turbine Blade Stage “
Work Experiences
• CFD Engineer: PT. Chroma International - Bandung, Indonesia (2017)
- Design and CFD analysis of a small-scale blow-down type of wind tunnel that can be operated with two flow conditions. Two flow conditions are achieved with two different nozzles: Supersonic Mach number of 2.0 and Subsonic Mach number of 0.6.
- Design and CFD analysis of axial turbine with 100 KW power output.
• Student researcher (Master’s and PhD): Renewable Energy Lab - Kookmin University (2019)
- Worked on satellite images to calculate cloud motion vector (CMV) using optical flow method and computer vision (Python/OpenCV) for solar irradiance forecasting.
- Estimated every minute time series solar radiation data in South Korea using deep learning models such as RNN, LSTM, GRU, and CNN.
- Successfully separated direct and diffuse irradiance from global horizontal irradiance by applying deep learning and transfer learning.
- Conducted research on deep learning models to forecast cloud fractions for very short-term forecast horizons using a sky camera.
- Solar irradiance, temperature, and humidity forecasting for energy saving of electric vehicles.
• Postdoctoral researcher: Renewable Energy Lab - Kookmin University (Sept 2024 - June 2025)
- Solar irradiance and cabin air temperature forecasting for moving electric vehicles.
• Postdoctoral researcher: Agricultural Facilities and Environment Lab - Chonnam National University (July 2025 - now)
- Livestock Transport 4.0: Eco-Friendly Animal Welfare Transport Solutions.
Published papers
2026
• Rial A. Rajagukguk, Rezi Delfianti, Se-Woon Hong, Indra Ardhanayudha Aditya, Arief Heru Kuncoro, Sudirman Palaloi, Nur Aryanto Aryono, La Ode Muhammad Abdul Wahid, Supratikno, Murbantan Tandirerung, Pranda M.P. Garniwa, Hyunjin Lee [“Feature Selection and Interpretability in Satellite-Based Solar Irradiance Estimation: Optimizing GEO-KOMPSAT-2A Multispectral Inputs for Tropical Environments”]. Engineered Science. 2026.
• Rial A. Rajagukguk, Jinseon Park, Heejou Kim, Chae-rin Lee, Se-yeon Lee, Ji-yeon Park, Taehwan Ha, Se-woon Hong. “Estimating Indoor Heat Stress in Livestock Facilities Using High-Resolution Geo-KOMPSAT-2A Satellite Data”. Journal of Agricultural Engineering. 2025.
• Se-yeon Lee, Ji-yeon Park, Jinseon Park, Chae-rin Lee, Rial A. Rajagukguk, Youngho Kang, Hyun Ho Noh, Se-woon Hong. “Field Evaluation of Human Exposure to Pesticides and Comparison with Exposure Assessment Models: Drone and Wide-area Sprayer Applications”. Agricultural and Environmental Sciences. 2026.
• Aditya, I. A., M. Soleh, H. Lee, P. M.P. Garniwa, M. F.B. Suhaimi, S.-W. Hong, Rial A. Rajagukguk. “Solar energy estimation in tropical environments: A novel framework for integrating satellite and sky imager data”. Energy Reports. 2026.
2025
• Rial A. Rajagukguk, Hoseong Lee, and Hyunjin Lee “Dynamic Solar Irradiance Estimation for Vehicle Thermal Management Using a Multi-Modal Machine Learning Framework”. Scientific Reports. 2025.
• Rial A. Rajagukguk, Se-yeon Lee, Ji-yeon Park, Kehinde FavourDaniel, Chae-rin Lee, ZhengChencDongLiu, TomásNorton, Jinseon Park, Se-woon Hong, “Deep learning for visual animal monitoring (Detection, Tracking, Pose Estimation, and Behavior Classification): A comprehensive review”. Smart Agricultural Technology. 2025.
• Rial A. Rajagukguk, Hyunjin Lee “Application of explainable machine learning for estimating direct and diffuse components of solar irradiance”. Scientific Reports. 2025.
• Rial A. Rajagukguk, Hyunjin Lee “Sky-Image-Based Sun-Blocking Index and PredRNN++ for Accurate Short-Term Solar Irradiance Forecasting”. Building and Environment. 2025.
2024
• Indra A. Aditya, Pranda M. Putra, Rial A. Rajagukguk, Yessy Asri “Estimating Irradiance through Satellite-Driven Deep Learning Models”. International Seminar on Intelligent Technology and Its Applications. 2024.
2023
• Rial A. Rajagukguk, Hyunjin Lee “Enhancing the performance of solar radiation decomposition models using deep learning”. Journal of the Korean Solar Energy Society. 2023.
2022
• Pranda M. Putra, Rial A. Rajagukguk, R. Kamil, Hyunjin Lee “Intra-day forecast of global horizontal irradiance using optical flow method and long short-term memory model”. Solar Energy. 2022. • Rial A. Rajagukguk, Won-Ki Choi, Hyunjin Lee “Sun blocking index (SBI) from sky image to estimate solar irradiance”. Building and Environment. 2022.
2021
• Rial A. Rajagukguk, R. Kamil, Hyunjin Lee “A deep learning model to forecast solar irradiance using a sky camera”. Applied Sciences 11 (11), 5049. 2021.
2020
• Rial A. Rajagukguk, Raden A. A. Ramadhan, Hyunjin Lee “A review on deep learning models for forecasting time series data of solar irradiance and photovoltaic power”. Energies 13 (24), 6623. 2020.
Working papers
• “Solar Irradiance Estimation in a Tropical Environment using Selected Spectral Satellite Images: A Case Study in Indonesia”. (Submitted)
• “An Outside-In Framework for Estimating Indoor Heat Stress in Broiler and Swine Farms Using GK2A Satellite Data”. (Submitted)
• “Assessment of hydrocyclone inlet direction on particle separation using CFD and field validation”.
Project
•Perusahaan Listrik Negara (PT PLN) Jakarta, Indonesia
- Solar irradiance estimation using sky camera. 6/2023-11/2023
- Solar irradiance forecasting using sky camera and satellite image. 5/2024-present
•Korea Evaluation Institute of Industrial Technology (KEIT) Seoul, Korea
- Thermal management system to reduce energy consumption and optimize the mileage of electric vehicle (EV). 4/2022-12/2025
•National Research Foundation of Korea (NRF) Seoul, Korea
- Machine learning linked solar radiation model to predict solar irradiance. 3/2019-2/2023
•SONUSYS Co., Ltd Seoul, Korea
- Controlling the window based on solar radiation components. 4/2021-10/2021
AWARD
• Best Paper Award with Prof. Hyunjin Lee, The Korean Solar Energy Society (KSES) 2023, Yeosu, Seoul, South Korea. 8 November 2023.
PATENT
• 구름 특성 기반 일사량 추정 시스템 및 방법. KOREAN INTELLECTUAL PROPERTY OFFICE. 2024.
International Conferences
• The American Society of Mechanical Engineers Energy Sustainability (ASME ES 2023). The Madison Hotel, Washington, DC, July 10 – 12, 2023. Presentation: “Minute-level solar irradiance estimation via sun-blocking index derived from sky images”.
• The 11th Asia-Pasific Forum in Renewable Energy (AFORE 2022). Ramada Plaza Jeju, South Korea, September 27 – October 1, 2022. Presentation: “Estimation of minute level of solar irradiance using sun-blocking index (SBI) derived from sky images”.
• Second Asian Conference on Thermal Sciences (2nd ACTS). Japan, October 3 – 7, 2021. Presentation: “Evaluation of decomposition models to estimate direct normal irradiance using sub-hour data”.