Geun Young Yun

4.4k total citations
78 papers, 3.4k citations indexed

About

Geun Young Yun is a scholar working on Building and Construction, Environmental Engineering and Health, Toxicology and Mutagenesis. According to data from OpenAlex, Geun Young Yun has authored 78 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Building and Construction, 49 papers in Environmental Engineering and 17 papers in Health, Toxicology and Mutagenesis. Recurrent topics in Geun Young Yun's work include Building Energy and Comfort Optimization (55 papers), Urban Heat Island Mitigation (39 papers) and Urban Green Space and Health (12 papers). Geun Young Yun is often cited by papers focused on Building Energy and Comfort Optimization (55 papers), Urban Heat Island Mitigation (39 papers) and Urban Green Space and Health (12 papers). Geun Young Yun collaborates with scholars based in South Korea, Australia and United Kingdom. Geun Young Yun's co-authors include Koen Steemers, M. Santamouris, Jack Ngarambe, Jeong Tai Kim, Mike McEvoy, Indira Adilkhanova, Abdo Abdullah Ahmed Gassar, Paul Tuohy, Je Hyeon Lee and Sumin Kim and has published in prestigious journals such as Renewable and Sustainable Energy Reviews, PLoS ONE and The Science of The Total Environment.

In The Last Decade

Geun Young Yun

77 papers receiving 3.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Geun Young Yun South Korea 33 2.4k 1.7k 582 500 459 78 3.4k
Salvatore Carlucci Norway 29 3.2k 1.3× 1.8k 1.1× 351 0.6× 295 0.6× 477 1.0× 75 3.9k
Deo Prasad Australia 30 1.6k 0.7× 1.7k 1.0× 889 1.5× 369 0.7× 436 0.9× 101 3.1k
Shady Attia Belgium 40 4.1k 1.7× 2.4k 1.4× 575 1.0× 272 0.5× 603 1.3× 252 5.1k
Ferdinando Salata Italy 33 2.3k 1.0× 2.2k 1.3× 1.0k 1.7× 497 1.0× 322 0.7× 75 3.4k
Ardeshir Mahdavi Austria 33 3.7k 1.5× 1.8k 1.0× 413 0.7× 458 0.9× 520 1.1× 291 4.6k
Steve Sharples United Kingdom 32 2.1k 0.8× 2.2k 1.3× 779 1.3× 500 1.0× 314 0.7× 142 3.5k
Roberto Lamberts Brazil 38 4.2k 1.7× 2.6k 1.5× 470 0.8× 196 0.4× 605 1.3× 166 5.1k
Stefano Paolo Corgnati Italy 36 4.1k 1.7× 1.8k 1.1× 387 0.7× 211 0.4× 740 1.6× 173 5.1k
Sigrid Reiter Belgium 28 2.6k 1.1× 1.8k 1.0× 271 0.5× 194 0.4× 489 1.1× 107 3.6k
Yixing Chen China 29 2.7k 1.1× 1.5k 0.9× 177 0.3× 308 0.6× 468 1.0× 94 3.5k

Countries citing papers authored by Geun Young Yun

Since Specialization
Citations

This map shows the geographic impact of Geun Young Yun's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Geun Young Yun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Geun Young Yun more than expected).

Fields of papers citing papers by Geun Young Yun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Geun Young Yun. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Geun Young Yun. The network helps show where Geun Young Yun may publish in the future.

Co-authorship network of co-authors of Geun Young Yun

This figure shows the co-authorship network connecting the top 25 collaborators of Geun Young Yun. A scholar is included among the top collaborators of Geun Young Yun based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Geun Young Yun. Geun Young Yun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Raj, Sarath, et al.. (2025). Adaptive neural temporal hybridization for missing data imputation in building energy use datasets: An integrated LNN-LSTM weighted model. Journal of Building Engineering. 112. 113774–113774. 1 indexed citations
2.
Huang, Boze, Jinda Qi, Minal Pathak, et al.. (2025). Climate-driven transformations: A framework for the sustainable urban landscape system to enhance heat resilience. Sustainable Cities and Society. 131. 106684–106684. 2 indexed citations
3.
Ngarambe, Jack, Sarath Raj, & Geun Young Yun. (2025). Subsurface urban heat islands: From prevalence and drivers to implications for geothermal energy and a proposed new framework based on machine learning. Sustainable Cities and Society. 120. 106153–106153. 4 indexed citations
4.
Raj, Sarath, et al.. (2025). Contrasting urban heat disparities across income levels in Seoul and London. Sustainable Cities and Society. 121. 106215–106215. 4 indexed citations
5.
Adilkhanova, Indira, Ji Hwan Jeong, & Geun Young Yun. (2025). The role of geographic scale of weather data in urban building energy models. Sustainable Cities and Society. 125. 106339–106339. 1 indexed citations
6.
Ngarambe, Jack, et al.. (2025). Integrating deep learning into quantile regression models for enhanced building energy benchmarking. Journal of Building Engineering. 109. 113044–113044.
7.
Choi, Young Jae, et al.. (2025). Real-time ventilation control for indoor CO2 management using occupant information. Building and Environment. 285. 113568–113568. 1 indexed citations
8.
Ngarambe, Jack, et al.. (2024). Causal effects of policy and occupant behavior on cooling energy. Renewable and Sustainable Energy Reviews. 206. 114854–114854. 3 indexed citations
9.
10.
Feng, Jie, Kai Gao, Hassan Saeed Khan, et al.. (2023). Overheating of Cities: Magnitude, Characteristics, Impact, Mitigation and Adaptation, and Future Challenges. Annual Review of Environment and Resources. 48(1). 651–679. 15 indexed citations
11.
Ngarambe, Jack, et al.. (2022). Geographically extended occupant clothing behavior model using convolutional neural networks with hyperband technique. Journal of Building Engineering. 49. 104023–104023. 5 indexed citations
12.
Ngarambe, Jack, et al.. (2020). Synergies between urban heat island and heat waves in Seoul: The role of wind speed and land use characteristics. PLoS ONE. 15(12). e0243571–e0243571. 66 indexed citations
13.
Santamouris, M. & Geun Young Yun. (2020). Recent development and research priorities on cool and super cool materials to mitigate urban heat island. Renewable Energy. 161. 792–807. 149 indexed citations
14.
Ngarambe, Jack, Geun Young Yun, & M. Santamouris. (2020). The use of artificial intelligence (AI) methods in the prediction of thermal comfort in buildings: energy implications of AI-based thermal comfort controls. Energy and Buildings. 211. 109807–109807. 194 indexed citations
15.
Kim, Sumin, Jae D. Chang, Geun Young Yun, & Sughwan Kim. (2017). Polymer Composites for Passive Control System of Buildings. International Journal of Polymer Science. 2017. 1–1. 1 indexed citations
16.
Yun, Geun Young, Je Hyeon Lee, & Inhan Kim. (2016). Dynamic target high pressure control of a VRF system for heating energy savings. Applied Thermal Engineering. 113. 1386–1395. 18 indexed citations
17.
Yun, Geun Young, et al.. (2011). Evaluation of Daylighting Effectiveness and Energy Saving Potentials of Light-Pipe Systems in Buildings. Indoor and Built Environment. 21(1). 129–136. 33 indexed citations
18.
Yun, Geun Young & Koen Steemers. (2011). Behavioural, physical and socio-economic factors in household cooling energy consumption. Applied Energy. 88(6). 2191–2200. 186 indexed citations
19.
Yun, Geun Young & Koen Steemers. (2010). Night-time naturally ventilated offices: Statistical simulations of window-use patterns from field monitoring. Solar Energy. 84(7). 1216–1231. 43 indexed citations
20.
Yun, Geun Young & Koen Steemers. (2007). Time-dependent occupant behaviour models of window control in summer. Building and Environment. 43(9). 1471–1482. 233 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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