Innovative Research Award
| Jihoon Jang |
| Affiliation |
Korea Institute of Civil Engineering and Building Technology |
| Country |
South Korea |
| Scopus ID |
57204915562 |
| Documents |
7 |
| Citations |
226 |
| h-index |
6 |
| Subject Area |
Engineering |
| Event |
Global Innovation Technologist Awards |
Jihoon Jang
Korea Institute of Civil Engineering and Building Technology, South Korea
Jihoon Jang is an engineering researcher whose work focuses on intelligent building systems, building energy prediction, indoor environmental quality, and data-driven optimization techniques. His published studies demonstrate the integration of artificial intelligence, machine learning, and building energy management systems to improve operational efficiency and sustainability in modern buildings. With a Scopus profile containing seven indexed publications, 226 citations, and an h-index of six, his research has contributed to practical advances in energy-efficient building technologies and predictive analytics.[1]
Abstract
Jihoon Jang’s scholarly work centers on predictive building analytics, energy optimization, and intelligent HVAC operation. His publications demonstrate the practical application of artificial neural networks and long short-term memory (LSTM) models for forecasting heating energy demand and optimizing building operation schedules. These contributions support sustainable infrastructure by improving energy efficiency while maintaining occupant comfort.[2]
Keywords
Building Energy Management, Artificial Intelligence, HVAC Systems, LSTM Networks, Sustainable Engineering, Indoor Environmental Quality, Machine Learning, Energy Prediction.
Introduction
Growing interest in sustainable buildings has accelerated the development of predictive analytical methods capable of reducing energy consumption while maintaining indoor environmental performance. Jihoon Jang’s research contributes to this objective by combining engineering knowledge with artificial intelligence, producing practical solutions applicable to smart buildings and energy management systems.[3]
Research Profile
The research profile reflects interdisciplinary expertise spanning building engineering, thermal performance modeling, data analytics, and intelligent control technologies. Publications appear in internationally recognized journals including Energy and Buildings, Journal of Building Engineering, Sustainability, and Energies. Citation metrics indicate sustained academic visibility within engineering research communities.[1]
Research Contributions
- Developed LSTM-based prediction models for heating energy consumption in non-residential buildings.
- Applied artificial neural networks for predicting optimum heating schedules using BEMS datasets.
- Investigated HVAC cooling set-point optimization considering mean radiant temperature.
- Improved thermal energy prediction through advanced feature selection methods.
- Contributed to affordable image sensing technologies for indoor environmental quality monitoring.
Publications
- Prediction of heating energy consumption with operation pattern variables using LSTM networks (2022) — 136 citations.
- Prediction of optimum heating timing utilizing BEMS data (2019) — 54 citations.
- Cooling set-point temperature considering mean radiant temperature (2019) — 35 citations.
- Improved model for predicting building thermal energy consumption (2019) — 23 citations.
- Collection and utilization of indoor environmental quality information using image sensing technology (2022) — 22 citations.
Research Impact
The citation performance of Jihoon Jang’s publications demonstrates consistent scholarly influence within engineering and building science. His studies provide methodological foundations for integrating machine learning into practical building operation, supporting energy conservation initiatives and digital transformation in infrastructure management. The combination of predictive modeling and environmental sensing has relevance for future smart-city applications.[4]
Award Suitability
Based on available scholarly indicators, publication quality, and demonstrated engineering contributions, Jihoon Jang’s work aligns with the objectives of the Global Innovation Technologist Awards. His research emphasizes innovation, measurable academic impact, and practical engineering applications, making the profile suitable for consideration within technology-focused academic recognition programs.[5]
Conclusion
Jihoon Jang has established a focused research portfolio addressing intelligent building operation, predictive analytics, and sustainable engineering. Through contributions to high-quality journals and meaningful citation impact, his work supports continued progress toward energy-efficient infrastructure and evidence-based building management technologies.
External Links
References
- Elsevier. (n.d.). Scopus author details: Jihoon Jang, Author ID 57204915562.
https://www.scopus.com/authid/detail.uri?authorId=57204915562
- Jang J. et al. (2022). Prediction of heating energy consumption with operation pattern variables for non-residential buildings using LSTM networks.
https://doi.org/10.1016/j.enbuild.2021.111647
- Journal of Building Engineering. (2019). Prediction of optimum heating timing based on artificial neural network.
https://doi.org/10.1016/j.jobe.2018.12.010
- Sustainability. (2019). The derivation of cooling set-point temperature in an HVAC system.
https://doi.org/10.3390/su11195417
- Global Innovation Technologist Awards. (n.d.). Official Award Website.
innovationtechnologist.com