About
The Building Energy Research Laboratory (BERL) at Columbia University harnesses advanced building physics, optimization techniques, and artificial intelligence to transform how we understand and regulate energy consumption in the built environment. Rooted in the Department of Mechanical Engineering, BERL focuses on decarbonization and electrification strategies for buildings, exploring everything from flexible HVAC integration and energy storage to community-scale micro-grids and equitable energy justice. Their work supports resilient, sustainable buildings that not only reduce operational costs but also improve occupant comfort, air quality, and urban climate outcomes.
Lab Director
Dr. Howard is the Director of the Columbia University Building Energy Research Laboratory. Her research interests are in using artificial intelligence and optimization tools to make decisions for the planning, design, and operation of decarbonized building energy systems. She has over 10 years of experience in the management and delivery of research outcomes.
News
BERL Lightning Talk at SimBuild 2026
Ryan Dubois will be presenting a preview of his work on his upcoming paper: Do Large Multimodal Models Understand Construction Drawings? An Evaluation of Visually Grounded Workflows during a lighting talk at SimBuild 2026. The full notes paper will be published as a part of the proceeding of BuildSys 2026 later this year.
Abstract:
BuildSys 2026 to Bring Together Global Research on Smart and Sustainable Built Environments
BuildSys 2026 will convene researchers and practitioners, such as Dr. Bianca Howard, working at the intersection of buildings, energy systems, and computing to share new methods and technologies for more efficient and responsive built environments. As part of the first ACM Sustainability Week, the conference emphasizes cross-disciplinary collaboration and systems-level thinking across buildings, cities, and transportation.
Evaluating the effectiveness, reliability and efficiency of a multi-objective sequential optimization approach for building performance design
This study, co-authored by Dr. Bianca Howard, evaluated a sequential optimization approach for building performance design that reduces computational effort without sacrificing solution quality. By optimizing building geometry, envelope, HVAC systems, and controls in stages, the method consistently identified high-performing design solutions while requiring far fewer simulations than traditional approaches. The findings suggest that sequential optimization can make advanced building performance analysis more practical for real-world design workflows.