Sungmin Yoon

2.6k total citations
117 papers, 2.0k citations indexed

About

Sungmin Yoon is a scholar working on Building and Construction, Industrial and Manufacturing Engineering and Environmental Engineering. According to data from OpenAlex, Sungmin Yoon has authored 117 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 78 papers in Building and Construction, 25 papers in Industrial and Manufacturing Engineering and 22 papers in Environmental Engineering. Recurrent topics in Sungmin Yoon's work include Building Energy and Comfort Optimization (67 papers), Wind and Air Flow Studies (19 papers) and Digital Transformation in Industry (17 papers). Sungmin Yoon is often cited by papers focused on Building Energy and Comfort Optimization (67 papers), Wind and Air Flow Studies (19 papers) and Digital Transformation in Industry (17 papers). Sungmin Yoon collaborates with scholars based in South Korea, China and United States. Sungmin Yoon's co-authors include Yuebin Yu, Jabeom Koo, Jiaqiang Wang, Doosam Song, Hyunwoo Lim, Quan Zhang, Peng Wang, Tianyi Zhao, Yong-Shik Kim and Jungmin Seo and has published in prestigious journals such as Renewable and Sustainable Energy Reviews, Applied Energy and Expert Systems with Applications.

In The Last Decade

Sungmin Yoon

110 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sungmin Yoon South Korea 27 1.2k 433 402 388 280 117 2.0k
Guannan Li China 31 1.2k 1.0× 232 0.5× 294 0.7× 707 1.8× 664 2.4× 81 2.3k
Haorong Li United States 32 1.3k 1.1× 138 0.3× 244 0.6× 389 1.0× 548 2.0× 103 2.6k
Yuebin Yu United States 28 1.0k 0.9× 115 0.3× 250 0.6× 216 0.6× 282 1.0× 55 2.0k
Mario Bergés United States 31 1.1k 0.9× 138 0.3× 134 0.3× 1.7k 4.4× 517 1.8× 144 3.2k
Srinivas Katipamula United States 19 1.4k 1.2× 114 0.3× 311 0.8× 644 1.7× 815 2.9× 83 2.3k
Jianli Chen United States 20 1.0k 0.9× 72 0.2× 518 1.3× 560 1.4× 151 0.5× 62 1.7k
Zhimin Du China 32 1.5k 1.3× 187 0.4× 266 0.7× 595 1.5× 883 3.2× 93 2.7k
Xinqiao Jin China 32 1.8k 1.6× 188 0.4× 380 0.9× 724 1.9× 957 3.4× 98 3.1k
Yunpeng Hu China 24 741 0.6× 116 0.3× 90 0.2× 331 0.9× 497 1.8× 57 1.5k

Countries citing papers authored by Sungmin Yoon

Since Specialization
Citations

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

Fields of papers citing papers by Sungmin Yoon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sungmin Yoon

This figure shows the co-authorship network connecting the top 25 collaborators of Sungmin Yoon. A scholar is included among the top collaborators of Sungmin Yoon 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 Sungmin Yoon. Sungmin Yoon 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.
2.
Yoon, Sungmin, et al.. (2025). Autonomous in-situ modeling for virtual building models in digital twins. Expert Systems with Applications. 278. 127289–127289. 2 indexed citations
3.
Yoon, Sungmin, et al.. (2025). AI agent-based indoor environmental informatics: Concept, methodology, and case study. Building and Environment. 277. 112879–112879. 4 indexed citations
4.
Yoon, Sungmin, et al.. (2025). In-situ backup virtual sensor application in building automation systems toward virtual sensing-enabled digital twins. Case Studies in Thermal Engineering. 66. 105792–105792. 2 indexed citations
5.
Wang, Jiaming, Peng Wang, Sungmin Yoon, et al.. (2025). Sensor fault diagnosis and calibration based on voting mechanism for online application using virtual in-situ calibration and time series prediction. Building and Environment. 278. 113040–113040. 1 indexed citations
6.
Yoon, Sungmin, et al.. (2025). Anomaly detection using convolutional autoencoder with residual gated recurrent unit and weak supervision for photovoltaic thermal heat pump system. Journal of Building Engineering. 100. 111694–111694. 2 indexed citations
7.
Yoon, Sungmin, et al.. (2024). GPT-based data-driven urban building energy modeling (GPT-UBEM): Concept, methodology, and case studies. Energy and Buildings. 325. 115042–115042. 16 indexed citations
8.
Wang, Peng, Junqing Sun, Sungmin Yoon, Liang Zhao, & Ruobing Liang. (2024). A global optimization method for data center air conditioning water systems based on predictive optimization control. Energy. 295. 130925–130925. 16 indexed citations
9.
Yoon, Sungmin, et al.. (2024). Virtual in-situ modeling between digital twin and BIM for advanced building operations and maintenance. Automation in Construction. 168. 105823–105823. 12 indexed citations
10.
Yoon, Sungmin, et al.. (2024). Brain-inspired learning rules for spiking neural network-based control: a tutorial. Biomedical Engineering Letters. 15(1). 37–55. 1 indexed citations
11.
Yoon, Sungmin, et al.. (2023). Prediction of pyrolysis kinetics for torrefied biomass based on raw biomass properties and torrefaction severity. Energy. 278. 127759–127759. 8 indexed citations
12.
Zhao, Tianyi, et al.. (2023). Strategies for sensor virtual in-situ calibration in building energy system: Sensor evaluation and data-driven based methods. Energy and Buildings. 294. 113274–113274. 17 indexed citations
13.
Kim, Jiwon & Sungmin Yoon. (2023). Virtual PMV sensor towards smart thermostats: Comparison of modeling approaches using intrusive data. Energy and Buildings. 301. 113695–113695. 11 indexed citations
14.
Wang, Jiaqiang, et al.. (2023). Sensor fault diagnosis and correction for data center cooling system using hybrid multi-label random Forest and Bayesian Inference. Building and Environment. 249. 111124–111124. 11 indexed citations
15.
Kim, Jiwon, et al.. (2023). In situ virtual sensing for dwelling infiltration rates in multi-unit residential buildings. Journal of Building Engineering. 69. 106225–106225. 7 indexed citations
16.
Yoon, Sungmin, et al.. (2023). In Situ Virtual Sensors in Building Digital Twins: Framework and Methodology. SSRN Electronic Journal. 14 indexed citations
17.
Yoon, Sungmin, et al.. (2023). The Mediating Effect of Grit and Career Preparation Behavior in the Relationship Between Emotional Intelligence and Career Adaptability in Adults. The Journal of Humanities and Social sciences 21. 14(2). 1043–1056.
18.
Liang, Ruobing, et al.. (2023). Realization of rule-based automated design for HVAC duct layout. Journal of Building Engineering. 80. 107946–107946. 1 indexed citations
19.
Yoon, Sungmin & Jechan Lee. (2023). Perspective for waste upcycling-driven zero energy buildings. Energy. 289. 130029–130029. 14 indexed citations
20.
Yoon, Sungmin, et al.. (2012). A Study on Building Energy Consumption Pattern Analysis Using Data Mining. KIEAE Journal. 12(2). 77–82. 2 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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