Research output per year
Research output per year
Personal profile
Education
2023 Ph.D., Seoul National University
2015 M.S., Seoul National University
2013 B.S., Seoul National University
2015 M.S., Seoul National University
2013 B.S., Seoul National University
Professional Experience
• (2015-2018) SamchullyES Co., Ltd. Senior Staff
• (2023-2023) Samsung Electronics Co., Ltd. Staff Engineer
• (2023-2025) Assistant professor of Department
of Energy and Environmental Engineering, Soonchunhyang University, South Korea
• (2025-present) Assistant professor of Department of Environment and Energy, Sejong
University, South Korea
• (2023-2023) Samsung Electronics Co., Ltd. Staff Engineer
• (2023-2025) Assistant professor of Department
of Energy and Environmental Engineering, Soonchunhyang University, South Korea
• (2025-present) Assistant professor of Department of Environment and Energy, Sejong
University, South Korea
Research interests
• Waste Management, Resource Circulation, Air Pollution, Particulate Matter, Machine learning
Major Research Achievements
• Studies on the integration of artificial intelligence for monitoring and predicting air pollution and wastes
• Development of smart environmental monitoring systems using machine learning and sensor fusion technologies
• Application of AI-based models for supporting decision-making in environmental policy and sustainable urban planning
• Development of smart environmental monitoring systems using machine learning and sensor fusion technologies
• Application of AI-based models for supporting decision-making in environmental policy and sustainable urban planning
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 11 Sustainable Cities and Communities
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Evaluating inter-site similarity and model transferability for machine learning prediction of CO2 and CH4 concentrations across urban typologies
Park, S., Eom, H., Lee, J., Lee, J., Jeong, K., Yi, S. M., Rim, D., Dai, Q., Jeong, S., Lee, Y. S. & Moonk, K. J., Mar 2026, In: Urban Climate. 66, 102830.Research output: Contribution to journal › Article › peer-review
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Imputing missing data with statistical-learning estimates: impacts on mortality risks attributable to area- and source-specific PM2.5.
Kim, Y., Kang, C., Yi, S. M., Heo, J. B., Kim, H., Lee, W., Kim, H., Hopke, P. K., Lee, Y. S., Shin, H. J., Park, J., Yoo, M., Jeon, K. & Park, J., Mar 2026, In: Atmospheric Pollution Research. 17, 3, 102785.Research output: Contribution to journal › Article › peer-review
Open Access1 Scopus citations -
Onshore winds amplify shipping PM2.5 exposure in a coastal megaport city: Insights from source apportionment and machine learning
Li, L., Dai, T., Bi, X., Song, S., Liu, B., Lee, Y. S., Xu, H., Dai, Q., Wu, J. & Feng, Y., 1 Apr 2026, In: Journal of Hazardous Materials. 507, 141752.Research output: Contribution to journal › Article › peer-review
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Preliminary Risk Assessment of Volatile Organic Compounds Near Industrial Complexes via Prediction of Degradation Products and Potential Toxicity
Oh, E., Choi, E. & Lee, Y. S., 2026, In: Journal of Korean Society for Atmospheric Environment. 42, 1, p. 73-89 17 p.Research output: Contribution to journal › Article › peer-review
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Coincidence effect of a low-cost particulate matter sensor: Observations from environmental chamber tests at diverse particle concentrations
Kim, K. T., Kim, H., Jeong, S., Lee, Y. S., Zhao, X. & Kim, J. Y., Sep 2025, In: Atmospheric Pollution Research. 16, 9, 102581.Research output: Contribution to journal › Article › peer-review
4 Scopus citations