Minhyun Lee

3.3k total citations · 1 hit paper
85 papers, 2.6k citations indexed

About

Minhyun Lee is a scholar working on Building and Construction, Renewable Energy, Sustainability and the Environment and Artificial Intelligence. According to data from OpenAlex, Minhyun Lee has authored 85 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Building and Construction, 25 papers in Renewable Energy, Sustainability and the Environment and 22 papers in Artificial Intelligence. Recurrent topics in Minhyun Lee's work include Building Energy and Comfort Optimization (41 papers), Solar Radiation and Photovoltaics (22 papers) and Sustainable Building Design and Assessment (17 papers). Minhyun Lee is often cited by papers focused on Building Energy and Comfort Optimization (41 papers), Solar Radiation and Photovoltaics (22 papers) and Sustainable Building Design and Assessment (17 papers). Minhyun Lee collaborates with scholars based in South Korea, Hong Kong and United States. Minhyun Lee's co-authors include Taehoon Hong, Choongwan Koo, Jimin Kim, Kwangbok Jeong, Hyuna Kang, Jaewook Jeong, Hyo Seon Park, Seungkeun Yeom, Changyoon Ji and Jongbaek An and has published in prestigious journals such as Environmental Science & Technology, Renewable and Sustainable Energy Reviews and The Science of The Total Environment.

In The Last Decade

Minhyun Lee

82 papers receiving 2.5k citations

Hit Papers

Energy consumption prediction and household feature analy... 2024 2026 2025 2024 20 40 60
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Energy consumption prediction and household feature analysis for different residential building types using machine learning and SHAP: Toward energy-efficient buildings
    2024 68 citations Xuerong Cui, Minhyun Lee et al. Energy and Buildings profile →

Peers

Minhyun Lee
Jimin Kim South Korea
Zhihua Zhou China
Choongwan Koo South Korea
Kwangbok Jeong South Korea
Steven K. Firth United Kingdom
Somayeh Asadi United States
Ian Beausoleil-Morrison Canada
Xin Zhou China
Arno Schlueter Switzerland
Jimin Kim South Korea
Minhyun Lee
Citations per year, relative to Minhyun Lee Minhyun Lee (= 1×) peers Jimin Kim

Countries citing papers authored by Minhyun Lee

Since Specialization
Citations

This map shows the geographic impact of Minhyun Lee'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 Minhyun Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minhyun Lee more than expected).

Fields of papers citing papers by Minhyun Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Minhyun Lee. 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 Minhyun Lee. The network helps show where Minhyun Lee may publish in the future.

Co-authorship network of co-authors of Minhyun Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Minhyun Lee. A scholar is included among the top collaborators of Minhyun Lee 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 Minhyun Lee. Minhyun Lee 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.
Jung, Seunghoon, S.S. Han, Jaewon Jeoung, et al.. (2025). Optimal planning of building integrated photovoltaic windows through room-level economic analysis. Energy and Buildings. 337. 115690–115690. 2 indexed citations
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Lee, Minhyun, Ji Luo, Mohammad Nyme Uddin, et al.. (2025). Dynamic thermal sensation model during speaking behaviours of occupants using machine learning. Energy and Buildings. 351. 116702–116702.
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Cui, Xuerong, et al.. (2025). Analyzing different household energy use patterns using clustering and machine learning. Renewable and Sustainable Energy Reviews. 212. 115335–115335. 2 indexed citations
6.
Kang, Hyuna, Hakpyeong Kim, Juwon Hong, et al.. (2024). Human-centered intelligent construction for sustainable cities. Automation in Construction. 168. 105788–105788. 4 indexed citations
7.
Kang, Hyuna, et al.. (2024). Harnessing sunlight beyond earth: Sustainable vision of space-based solar power systems in smart grid. Renewable and Sustainable Energy Reviews. 202. 114644–114644. 11 indexed citations
8.
Lee, Minhyun, et al.. (2024). Thermophysiological responses and thermal comfort of occupants in indoor spaces under different speaking and non-speaking conditions. Building and Environment. 260. 111682–111682. 6 indexed citations
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Cui, Xuerong, Minhyun Lee, Choongwan Koo, & Taehoon Hong. (2024). Energy consumption prediction and household feature analysis for different residential building types using machine learning and SHAP: Toward energy-efficient buildings. Energy and Buildings. 309. 113997–113997. 68 indexed citations breakdown →
11.
An, Jongbaek, et al.. (2024). Visual fatigue prediction using classification model based on physiological responses of occupants under office lightings. Journal of Building Engineering. 98. 111146–111146. 3 indexed citations
12.
Lee, Minhyun, et al.. (2024). Non-invasive vision-based personal comfort model using thermographic images and deep learning. Automation in Construction. 168. 105811–105811. 6 indexed citations
13.
Uddin, Mohammad Nyme, et al.. (2024). Predicting occupant energy consumption in different indoor layout configurations using a hybrid agent-based modeling and machine learning approach. Energy and Buildings. 328. 115102–115102. 7 indexed citations
14.
Uddin, Mohammad Nyme, Minhyun Lee, & Meng Ni. (2023). The impact of socio-demographic factors on occupants’ thermal comfort and sensation: An integrated approach using statistical analysis and agent-based modeling. Building and Environment. 246. 110974–110974. 10 indexed citations
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Lee, Minhyun, et al.. (2023). Grid parity analysis of photovoltaic systems considering feed-in tariff and renewable energy certificate schemes in Hong Kong. Renewable and Sustainable Energy Reviews. 181. 113326–113326. 26 indexed citations
17.
Lee, Minhyun, et al.. (2023). Peer-to-peer trading price and strategy optimization considering different electricity market types, tariff systems, and pricing models. Energy and Buildings. 300. 113645–113645. 9 indexed citations
18.
Lee, Minhyun, et al.. (2023). Optimization of Feed-in Tariff mechanism for residential and industrial photovoltaic adoption in Hong Kong. Journal of Cleaner Production. 406. 137043–137043. 6 indexed citations
19.
Lee, Minhyun, et al.. (2022). Development of a preliminary environmental risk assessment system by using text mining for introducing alien crops. Journal of Environmental Management. 311. 114794–114794. 2 indexed citations
20.
Kim, Jimin, Taehoon Hong, Jaemin Jeong, et al.. (2018). Multi-criteria decision support system of the photovoltaic and solar thermal energy systems using the multi-objective optimization algorithm. The Science of The Total Environment. 659. 1100–1114. 20 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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