Director of the AI+HPBAssistant Professor Research Fellow3rd Year Design CoordinatorUndergraduate curriculum committee member IBPSA-Houston chapter president


Updated 12/30/22 (My CV is available at this link )


Dr. Rania Labib is an accomplished Assistant Professor at Prairie View A&M University, part of the Texas A&M University system. As the founder and director of the Artificial Intelligence for High-Performance Buildings Lab (AI + HPB), she expertly blends her knowledge in energy-efficient buildings, building performance standards (BPS), energy modeling and simulations, energy management, buildings energy codes, AI, and big data to advance STEM education and research. 

Dr. Labib's impressive academic background includes a Ph.D. from Texas A&M University in Architecture, where she specialized in integrating Internet of Things technologies into building facades for energy efficiency and occupant comfort. She has further expanded her expertise by participating in Stanford University's prestigious Energy Innovation and Emerging Technologies Program at the School of Engineering (anticipated completion June 2023) and is set to complete her Certified Energy Manager (CEM) certification by May 2023. 

With over 13 years of experience in research, education, and architecture practice, Dr. Labib has established herself as an expert in various subjects, such as building energy analysis and modeling, energy codes, energy management, building electrification and decarbonization, digital twins, advanced built environment modeling and simulation tools, environmental inequality, indoor air quality, building automation, computer science, AI, solar -energy calculations, and big data. 

Dr. Labib's numerous accomplishments include an honorable mention in the 2016 National Science Foundation's Graduate Research Fellowship Program and serving as the current president of the IBPSA-USA Houston Chapter, which recently received the 2022 IBPSA-USA Outstanding Chapter Award. She has authored and co-authored numerous scientific publications, presenting her research work both nationally and internationally. Her work encompasses machine learning-enabled building performance simulations, computer vision recognition, high-performance computing, and daylighting and visual comfort of indoor spaces. 

Dr. Labib is affiliated with ASHRAE, IBPSA, and IES.