Dr. Samir Touzani is a Statistician Reaserach Scientist within the Building Technology and Urban Systems Division at Lawrence Berkeley National Laboratory. Dr. Touzani's research interests lie at the intersection of Machine Learning, Statistics and Energy Efficiency. Most of his current work focuses on developing data driven methods to solve energy performance analysis problems. Prior to joining LBNL, Dr. Touzani was a Research Scientist at the French Institute of Petroleum (IFP Energies Nouvelles) where he conducted research in the development of statistical learning and uncertainty quantification methods and tools for oil and gas reservoir engineering applications. He received a Master's degree in Physics from Pierre and Marie Curie University and a Ph.D. in Statistics from Joseph Fourier University.
Researchers in the Building Technology & Urban Systems Division (BTUS) at Lawrence Berkeley National Laboratory develop data and technologies that increase energy efficiency and improve the health, safety and comfort of building occupants, in the United States and worldwide.
We work closely with industry partners, academics and government officials to achieve these goals, and share our research widely.
We are at the forefront of cutting-edge research that redefines building technology and explores all areas of urban systems.
We have been leaders for decades in developing energy-efficient windows, improving indoor air quality, coming up with new ideas to fix the nation's electricity grid, and so much more.
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We offer a variety of technologies designed to simulate and model real-world circumstances to assist in energy-saving programs and help building owners build better buildings. These tools can help calculate performance of building systems like windows and shades, help consumers and builders pick the best windows for a variety of applications and much more.