“The conference will present cutting-edge strategies and technologies tailored to optimize energy conservation in hot climate regions, paving the way for a greener and more sustainable future,” said Walid Chakroun, Scientific Committee Chair.
This conference provides a forum for discussion of the latest research and development in the field of Indoor Environmental Quality in high ambient temperature climates. The objective of the conference is to facilitate a better understanding of the integration of energy efficiency in HVAC systems and IAQ in the high ambient temperature regions, focusing on the impact of low-energy design on occupant health in different building sectors for both developed and developing nations.
The conference technical program includes oral presentations and discussions of the accepted papers; lectures by invited speakers who have an excellent record and experience with IEQ/energy efficiency; and a panel discussion from experts and decision makers where recommendations and ideas of research can be generated for better design and preserving healthy environment.
Keynote Speakers

Dr. Yousef Alhorr, Founding Chairman of the GORD Institute
Keynote Topic: Innovative Multimode Ultra-Efficient Outdoor Cooling Systems: Synergia 9n1
Bio: The Gulf Organisation for Research and Development (GORD) established in 2009, led by a team of highly skilled, and multi-disciplinary committed experts, is proud of its leadership in the sustainability drive of the built environment. GORD has pioneered a comprehensive framework for green building certification specific to the needs of the region, through development and implementation of Global Sustainability Assessment System (GSAS) for building and infrastructure from micro and macro level perspectives. The multi-disciplinary scientific research programs of GORD aim to foster innovation, advance knowledge, share experiences and build networks to enhance the sustainability of the built environment. In addition, the human and institutional capacity building needed to synergize the efforts towards sustainable development has led GORD to adopt multi-dimensional capacity building approaches for addressing the needs of public, governments and businesses. I believe that the holistic sustainability approach embarked upon by GORD will contribute to the global effort to meet the needs of the present without compromising the rights of future generations.
Qingyan “Yan” Chen
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Qingyan “Yan” Chen is the Director of the PolyU Academy for Interdisciplinary Research (PAIR) and Chair Professor of Building Thermal Science in the Department of Building Environment and Energy Engineering at The Hong Kong Polytechnic University and Professor Emeritus of Mechanical Engineering at Purdue University, United States. He also served as the Editor-in-Chief of Building and Environment from 2008 to 2024.
Keynote Topic: Development and Application of a CFD-Based AI Model for Simulating Airflow and Pollution Dispersion around Buildings
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Description: Urban design necessitates accurate predictions of wind and contaminant dispersion to foster sustainable cities. Although computational fluid dynamics (CFD) models like large-eddy simulation (LES) offer precise predictions, they are computationally intensive. Steady Reynolds-averaged Navier-Stokes (SRANS) models are somewhat faster but suffer from inaccuracies due to the approximations involved. This study introduces a two-stage CFD-based artificial intelligence (AI) model that significantly reduces computational costs while maintaining high accuracy. The AI model employs a graph neural network (GNN) framework, using an SRANS model with a coarse grid as the initial state, and then refines the CFD outputs to achieve high-fidelity results in a single inference step. The GNN model was trained using data on airflow and contaminant dispersions across various scenarios with differing building structures and densities, incorporating corrections from key parameters derived from LES. When applied to predict airflow and contaminant dispersion in a section of Tokyo with available experimental data, the CFD-based GNN model produced results comparable to those of LES, while reducing computational costs by three orders of magnitude at the same grid resolution.
Registration for the Conference
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The early registration fee is $400 USD and includes, a reception, lunches, dinners, coffee breaks, banquet, tours, and the conference proceedings.
- Early registration ends February 21, 2025.
- The late registration fee is $520 USD. Late registration begins February 22, 2025.
- Registration for residence of Qatar $200 USD.
- The student registration fee is $100 USD.