RESEARCH INTERESTS

• Digital Twins and Advanced Modeling

• Building Information Modeling (BIM)

• Big Data & Data Analytics in the Built Environment

• Internet of Things (IoT) in Buildings

• Data Center Design

• Sustainability and ESG

• Building Automation Systems

• Advanced Simulations Tool Development (Software Dev.)

• Indoor Air Quality

• High-Performance Computing in Building Simulations

• Daylighting and Visual Comfort

• Artificial Intelligence and Machine Learning

• Large Language Models (LLM)- RAG, Fine Tunning, etc.

• Natural Language Processing (NLP)

Bio

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 (IoT) 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. Additionally, she recently completed a Certificate in Business Management for STEM professionals from Cornell University.

With over 14 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, and big data. Her leadership at the AI + HPB lab has driven significant advancements in integrating AI and computational tools for sustainable and intelligent building solutions.

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. Additionally, her research includes the development of custom Large Language Models (LLMs) fine-tuned with Retrieval-Augmented Generation (RAG) and Physics-Informed Neural Networks (PINNs) to advance daylighting simulations in buildings.

Dr. Labib's dedication to fostering strategic partnerships and developing innovative solutions has positioned her as a leading figure in the AEC industry. Her commitment to integrating cutting-edge technologies within diverse teams and projects underscores her ability to drive the future of sustainable design and construction.

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