Kyungmin Lee
Kyungmin Lee
Ph.D. in Energy and Environmental Policy
University of Delaware
Ph.D. in Energy and Environmental Policy
University of Delaware
Embedded Files
University of Delaware
Bio
Bio
Hello! I am Kyungmin Lee. I hold a Ph.D. in Energy and Environmental Policy at the Joseph R. Biden, Jr. School of Public Policy and Administration, University of Delaware. I have done research at the Urban Observatory under the guidance of Dr. Gregory Dobler at the Biden School of Public Policy and Administration, the Department of Physics and Astronomy, and the Data Science Institute. I am also a graduate fellow at the UD Data Science Institute and the Climate Hub.
My research focuses on energy policy, climate policy, urban sustainability, community development, and spatiotemporal data analysis using AI technologies. My main areas of expertise are computer vision and machine learning, particularly in the semantic scene understanding of remote sensing imagery. I am interested in exploring how AI can be used for data-driven policy development in the environmental field.
Research Areas
Computational Social Science
Data Science for Social Good
Machine Learning for Public Policy
Remote Sensing & AI (Deep Learning, Machine Learning, Computer Vision)
Mixed methods (Quantitative & Qualitative Analysis)
Research Projects
Research Projects
Evidence-Based Policy
Evidence-Based Policy
Data-Driven Policy
Data-Driven Policy
Energy Policy
Energy Policy
Energy-end User Behavior Pattern from Images/Video
Urban Energy Policy
Renewable Energy Policy
Environmental Policy
Environmental Policy
Global Climate / Carbon Neutrality Policy
Urban Heat Island Effect
Flood Risk
Air Quality
Diversity, Ethics & Inclusiveness
Diversity, Ethics & Inclusiveness
Data Privacy Preservation Model
Value Sharing Mechanism
Dissertation Description
Dissertation Description
My research project uses the Urban Observatory methodology for studying dynamics in complex urban systems through time-dependent proximal remote imaging to characterize urban energy metabolism related to energy-end user behavior, urban heat island effect, and data privacy via infrared imaging. This work applies machine learning and computer vision techniques for image processing and suggests data-driven policy design in energy and environmental policy.
Research & Teaching Philosophy
Research & Teaching Philosophy
When we understand the purpose behind studying a specific subject, we become self-motivated.
My pedagogical strategies emphasize critical thinking, encouraging students to recognize the value of the environment, connect it to their daily lives, and sustain a sense of curiosity.
I integrate research, teaching, and service through the lens of lifestyle practices rooted in observation. My work incorporates remote sensing technologies—ranging from satellite imagery to drones—as well as socioeconomic observations gathered through in-depth interviews and field surveys.
As a filmmaker, I also enjoy documenting my research through video, a passion that grew from a personal hobby.
For more information, please contact kmlee@udel.edu
For more information, please contact kmlee@udel.edu
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