报告题目：Data-Driven Building Performance Assessment and Climate-Responsive Design: Recent Research from Hanyang University
报 告 人：Associate Professor Minjae Shin
报告时间：2026年4月23日（周四）上午9:30
报告地点：谭山书院博雅讲堂
报告摘要：Buildings are expected to play a central role in achieving carbon reduction, energy efficiency, and occupant comfort under increasingly complex urban and climatic conditions. This special lecture introduces recent research conducted by graduate students in the Building Energy & Environment Research Group (BEERG) at Hanyang University, focusing on how data-driven and simulation-based approaches can improve building performance assessment and support climate-responsive design. The lecture presents four representative studies. First, an urban building energy modeling study examines how thermal zoning methods and window modeling influence energy prediction accuracy, highlighting the potential of a data-driven K-cluster zoning approach. Second, a building envelope study proposes an improved in-situ U-value assessment method that incorporates environmental variables to enhance the reliability of infrared thermography-based evaluation. Third, a future climate study investigates how downscaled weather data for Korea affect building energy use and indoor thermal comfort, and evaluates the effectiveness of retrofit strategies under future warming scenarios. Finally, a glare study explores the assessment of indoor visual discomfort caused by reflected sunlight from highly reflective façades, an issue of growing importance in dense urban environments. Together, these studies demonstrate how integrated modeling, measurement, and environmental analysis can support more accurate, resilient, and sustainable building design and operation.
报告人简介：Dr. Minjae Shin is a faculty member in the Department of Architectural Engineering at Hanyang University, South Korea. He earned his Ph.D. in Building Science and Engineering from Texas A&M University (2018), follwing an M.S. in Architectural Engineering from Hanyang University (2012), and a B.S. from the same institution (2010). His academic and professional journey includes roles as an Assistant Professor at the University of Alabama (2018–2020) and research positions at the Texas A&M Energy Systems Laboratory (2013–2018). Dr. Shin specializes in building performance optimization, energy-efficient HVAC systems, and sustainable architectural design. His research integrates advanced technologies such as deep reinforcement learning, UAV-based 3D modeling, and automated thermal zoning to enhance energy efficiency and occupant comfort. He has authored over 20 peer-reviewed articles in leading journals. His work bridges computational innovation with practical solutions, advancing sustainable and resilient building practices globally.
