Arfa Aijazi

building performance simulations, data visualization, machine learning, and climate change adaptability.

B.S. in Materials Science and Engineering from Massachusetts Institute of Technology (2013)
M.S. in Building Technology from Massachusetts Institute of Technology (2017)

Arfa Aijazi is a PhD student in Building Science in Architecture at the University of California, Berkeley, and also works as a graduate student researcher at the Center for the Built Environment. She received a Masters in Building Technology (2017) and Bachelors in Materials Science and Engineering (2013) from the Massachusetts Institute of Technology. Her doctoral research evaluates how climate change impacts building performance by using future weather files in existing simulation tools in order to design more climate resilient buildings.

Nagpal, Shreshth, Caitlin Mueller, Arfa Aijazi, and Christoph F. Reinhart. “A Methodology for Auto-Calibrating Urban Building Energy Models Using Surrogate Modeling Techniques.” Journal of Building Performance Simulation, April 5, 2018, 1–16. https://doi.org/10.1080/19401493.2018.1457722.

Aijazi, Arfa N., and Leon R. Glicksman. “Comparison of Regression Techniques for Surrogate Models of Building Energy Performance.” In ASHRAE and IBPSA-USA SimBuild, 2016.