Pengyuan Shen

Ph.D, associate professor, Shenzhen overseas high-level talent, Shenzhen Nanshan District Piloting Talent, and young editor of Building Simulation journal. He Graduated from the Department of Building Environment and Equipment Engineering of Tongji University, and obtained a Ph.D. in Architecture from the University of Pennsylvania in 2018. He worked in the Department of Architecture of Harbin Institute of Technology (Shenzhen) from 2018 to 2024, and joined Tsinghua University Shenzhen International Graduate School in November 2024. He has presided over and participated in a number of national, provincial and municipal longitudinal scientific research projects. At present, he has published more than 30 journal papers as the first author or corresponding author. His main research directions include building performance and thermal comfort, climate change and urban climate adaptability, and the application of artificial intelligence and machine learning in parametric green building design.

Our research group is currently recruiting 2 postdoctoral fellows. At the same time, we recruit 1 doctoral student and several master's students every year. Students with computer, HVAC, geographic information, and architectural and urban planning backgrounds who are interested in creating a future climate-adaptive human settlement are welcome to join our research group.

Sep. 2012 – May. 2018  University of Pennsylvania, Architecture , PhD

Sep. 2006 – Jun. 2010.6  Tongji University, Building , Building Environment and Engineering, Bachelor

Nov. 2024 - Present, Associate Professor, Shenzhen International Graduate School, Tsinghua University

Jan. 2022 - Oct. 2024, Associate Professor, Harbin Institute of Technology (Shenzhen)

Sep. 2018 - Dec. 2021, Assistant Professor, Harbin Institute of Technology (Shenzhen)

Jan. 2018 - May 2018, Project Manager, Country Garden Group

Aug. 2011 - Aug. 2012, Research Assistant, School of Mechanical Engineering, Tongji University

July 2010 - July 2012, Assistant Engineer, Shanghai Academy of Building Research

Building Simulation, Youth Editorial Board;

Buildings, Guest Editor

Our team is dedicated to advancing building performance, comfort, and sustainability in response to evolving urban and climate dynamics. My interdisciplinary approach combines architectural design, engineering, and data-driven technologies to enhance building efficiency, resilience, and human-centric environments. At the core of my research, I focus on building energy efficiency, urban climate adaptability, and occupant comfort, often incorporating artificial intelligence and machine learning to optimize performance-driven design strategies.

An important aspect of our team’s work is adapting buildings and urban infrastructure to climate change, particularly through developing predictive models that inform energy retrofits and resilience strategies. By employing and developing advanced modeling and simulation methods and tools, such as microclimate simulations and multi-objective optimization frameworks, my research addresses the potential impacts of future climate conditions and urban heat islands on building energy demands and thermal comfort. Such approaches include coupling climate models with building simulations to optimize energy use and enhance sustainability in high-density urban settings. The contributions extend to improving urban thermal environments, where we investigated microclimate interventions and their impact on outdoor thermal comfort. This research is particularly relevant in tropical and subtropical regions, where urban heat and climate change exacerbates the need for effective cooling strategies. Related projects aim to establish guidelines and decision-support tools that help city planners and architects mitigate the urban heat island effect through intelligent urban design and passive cooling measures.

Another significant area of our research is applying machine learning to performance-driven design. By leveraging data analytics, we developed automated frameworks for evaluating and optimizing various building performance parameters, such as energy consumption, daylighting, and thermal comfort. The models that we developed also contribute to occupant-centric design, addressing how behavioral patterns impact energy use and comfort, with particular emphasis on visual and thermal conditions in built environments like sports facilities and office spaces. My roles in collaborative projects emphasize cross-disciplinary efforts to address environmental challenges, making the involved research pivotal for advancing sustainable architecture and urban resilience in rapidly urbanizing areas.

1. Shen P*. Building retrofit optimization considering future climate and decision-making under various mindsets. Journal of Building Engineering. 2024;96:110422. (WOS Q1, IF: 6.7)

2. Shen P*, Wang M, Liu J, Ji Y. Hourly air temperature projection in future urban area by coupling climate change and urban heat island effect. Energy and Buildings. 2023;279:112676. (WOS Q1, IF: 7.2)

3. Shen P*, Liu J, Wang M. Fast generation of microclimate weather data for building simulation under heat island using map capturing and clustering technique. Sustainable Cities and Society. 2021;71:102954.

4. Shen P, Yang B*. Projecting Texas energy use for residential sector under future climate and urbanization scenarios: A bottom-up method based on twenty-year regional energy use data. Energy. 2020;193:116694. (WOS Q1, IF: 8.9)

5. Shen P*;Braham William; Yi Yunkyu, The feasibility and importance of considering climate change impacts in building retrofit analysis, Applied Energy, 2019, 233-234: 254~270 (WOS Q1, IF: 11.4)