Our Speakers

Xin Zhou is an Associate Professor at the School of Architecture, Southeast University. Her research focuses on building and urban energy modeling, occupant behavior, building energy sufficiency and flexibility, and multi-scale building performance simulation. She serves as a Subject Editor of Building Simulation and an Editorial Board Member of Energy and Buildings, and is a voting member of ASHRAE SSPC 140 and TC 7.10. She received the IBPSA Outstanding Young Contributor Award in 2019.

Urban residential cooling demand is shaped not only by building physics, but also by heterogeneous occupant behavior and how cooling supply is matched to actual needs. This presentation introduces a bottom-up urban building energy modeling framework that integrates building physics, occupant AC-use behavior, supply-demand matching, and demand response. Using residential cooling as a case study, it examines how different levels of energy sufficiency affect urban cooling consumption, peak loads, and demand heterogeneity, and further discusses the trade-off between reducing baseline energy demand and maintaining short-term demand flexibility.

Dr. Shohei Miyata is a Project Lecturer in the Department of Architecture, School of Engineering, The University of Tokyo, a position broadly comparable to Assistant Professor in the U.S. His research focuses on HVAC systems and smart buildings, with particular interests in system emulation, control optimization, fault detection and diagnosis, and semantic technologies. He has received several best paper awards from SHASE, AIJ, and previous ASim conferences. He also served as a Co-Chair of ASim2024, held in Osaka, Japan.

Smart buildings require both advanced control technologies and scalable deployment of diverse applications. These two goals call for seemingly contrasting modelling approaches. Detailed simulation and emulation provide concrete representations of building systems for developing and testing advanced controls, while semantic and data models abstract system-specific information to enable interoperability and scalable applications. Drawing on our research spanning both perspectives, this talk explores the roles of concretization and abstraction in modelling HVAC systems, with reference to recent developments in Japan. It discusses how these complementary approaches can shape the future of smart building research and practice.

Federico Tartarini is a Senior Lecturer in the School of Architecture, Design and Planning at the University of Sydney and recipient of the 2025 ASHRAE Ralph G. Nevins Physiology & Human Environment Award. His research spans thermal comfort and heat-health across diverse populations. He develops globally used open-source tools, including pythermalcomfort and HeatWatch, and contributes to the Lancet Countdown on health and climate change. He proposes "fan-first" cooling in buildings as a primary strategy for a warming world.

Current building performance simulations primarily assess occupants using thermal sensation models. However, tested against large field datasets, standard PMV formulations predict sensation correctly only about a third of the time, and were never designed to evaluate thermal safety. This talk separates thermal sensation from physiological strain, clarifies when each model applies, and demonstrates how thermophysiological models can be computed directly from simulation outputs using open-source tools. It concludes by advocating for air movement as a primary cooling strategy and poses open questions for the IEQ community in a warming climate.

Filip Biljecki is an Associate Professor at the NUS Department of Architecture. He received his PhD and MSc from TU Delft. His research and teaching integrate urban data science, geomatics, and geospatial technologies to advance urban digital twins and data-driven urban planning. Filip serves the community through associate editor roles in two journals: Computers, Environment and Urban Systems & Landscape and Urban Planning.

The Urban Analytics Lab at the National University of Singapore has a holistic commitment to urban informatics: not just conducting analytical research but building an ecosystem that supports sustainable and human-centered development of the field and cross-pollination with other domains. This agenda includes foundational research such as advancing data quality assessments, open data benchmarking, and investigations on crowdsourcing, alongside structural developments including tools, datasets, standards, and community initiatives. This presentation will focus on the group’s open science efforts, and it will provide a high-level overview of recent open-source software, open datasets, and other initiatives fostering reproducibility.

Dorit Aviv is an Associate Professor of Architecture at the University of Pennsylvania’s Weitzman School of Design, where she directs the Thermal Architecture Lab. Her research explores innovative approaches to cooling buildings and cities, integrating architectural design, thermodynamics, and materials science. Aviv is a licensed architect and holds a PhD in Architectural Technology from Princeton University. Her built prototypes for passive and low-energy cooling have received major awards, including a Holcim Award for Sustainable Construction in 2021 and an AIA New York State Design Award in 2026.

The increasing frequency and intensity of heat waves have made extreme heat the deadliest climate-related hazard globally, disproportionately affecting vulnerable urban communities. As architects, engineers, and building scientists grapple with the challenge of keeping people cool, considerations of resilience, carbon footprint, and social impact must remain central to the development of cooling solutions, alongside technological innovation. This talk will present three projects that address urban heat through architectural design, modeling, prototyping, and testing in real-world environments, exploring how collaboration with communities and civic partners can inform the development of more resilient and sustainable approaches to cooling.

Marco Savino Piscitelli is an Assistant Professor in Building Physics at the Department of Energy, Politecnico di Torino. After graduating in Building Engineering in 2014, he began his PhD in Energetics and visited The Hong Kong Polytechnic University in 2018. Named a Siebel Scholar in 2019, he earned his PhD in 2020. He is Operation Manager of the BAEDA Lab, focused on AI-based decision support for building energy management, and teaches HVAC system management and building automation.

Building energy management increasingly relies on data scattered across automation systems, sensors, models, and technical documentation. This fragmentation limits the scalable deployment of advanced analytics, control, and decision support. This presentation explores how semantic technologies and AI can tackle the problem together. Ontologies and knowledge graphs offer a machine-interpretable representation of building systems, data, and application requirements, while LLM-based agents help create semantic models, configure applications, query data, and interpret analytical results. At the same time, semantic models ground AI in building-specific context, making energy management applications more reliable, interpretable, and portable.

Ellie Jungmin Han is an Assistant Professor at Yonsei University and a former lecturer at Harvard GSD and fellow at the Harvard Center for Green Buildings and Cities. She holds a Doctor of Design from Harvard GSD. Her research combines physics-based simulation, AI, and quantum methods for sustainable buildings and cities, focusing on urban energy modeling, digital twins, retrieval-augmented design reasoning, and optimization to connect performance prediction with architectural decisions.

How can building simulation become an active design partner? This invited talk presents research at Yonsei University’s DataXDesign Lab integrating physics-based simulation, artificial intelligence, and emerging quantum methods across buildings, campuses, and cities. Applications include urban energy modeling, campus digital twins, retrieval-augmented design reasoning, and quantum optimization for microgrid energy allocation. Surrogate models and climate-informed design tools connect performance prediction with architectural decisions. Addressing calibration, uncertainty, and physical consistency, the talk explores how knowledge retrieval, simulation, and optimization can jointly support sustainable design and operation.