Events Calendar

From Research to Practice: Scaling Building Envelope Intelligence with AI

What does it take to turn deep academic research into a scalable technology platform? In this talk, the co-founders of Lamarr.AI reflect on a decade-long interdisciplinary collaboration spanning both academia and industry, culminating in a commercial AI platform for building envelope intelligence. The presentation will highlight the technical breakthroughs, system design choices, and hard lessons learned while translating research into real-world impact. This talk will offer insights for researchers, practitioners, and innovators working at the intersection of AI, sustainability, and the built environment.

About the Speakers:

Tarek Rakha, Ph.D.

Dr. Tarek Rakha is a scholar-practitioner working at the intersection of building science, artificial intelligence, and climate resilience. He holds a Ph.D. in Building Technology from MIT and has spent over a decade leading federally funded research focused on building envelopes, urban energy systems, and environmental performance diagnostics. A Regent’s Innovator on leave as Associate Professor and Director of the High Performance Building Lab at Georgia Tech, his work bridges theory and practice by operationalizing research outcomes into scalable, field-tested technologies used by cities, universities, healthcare systems, and building owners.

Senem Velipasalar, Ph.D.

Dr. Senem Velipasalar is an expert in machine learning, computer vision, and intelligent sensing systems, with a research career spanning academia and applied technology development. She received her Ph.D. from Princeton University and is a Professor in the Electrical Engineering and Computer Science Department at Syracuse University, where she leads the Smart Vision Systems Lab. Her research has been recognized with numerous honors, including an NSF CAREER Award, the IEEE Region 1 Technological Innovation Award, and the TACNY 2025 Technologist of the Year Award. Dr. Velipasalar’s work focuses on designing robust ML systems that move beyond laboratory settings into production environments, with applications across infrastructure, mobility, and the built environment.