Dr Becerik-Gerber is an associate professor at the Astani Department of Civil and Environmental Engineering of University of Southern California. Her research falls at the intersection of built environments, machine intelligence, and systems thinking. Specifically, her work focuses on the development of novel methods for the acquisition, modelling, and analysis of the data needed for cognitive (responsive and adaptive) built environments that can perceive, sense, reason and collaborate with their users, and support decision-making, problem solving, and management of resources.
Using multi-dimensional data, she develops algorithms, frameworks and visualisation techniques to improve built-environment resiliency, efficiency, sustainability, and maintainability while increasing user satisfaction. She is the founding director of the Innovation in Integrated Informatics Lab: http://i-lab.usc.edu/ .
Her work has received support worth approximately USD $5 million from a variety of sources. She serves as an associate editor for ASCE’s Journal of Computing in Civil Engineering since 2011. In 2012, she was appointed as the inaugural holder of the Stephen Schrank Early Career Chair in Civil and Environmental Engineering.
She is also the recipient of MIT Technology Review’s TR35 Recognition (2012), NSF CAREER Award (2014), Viterbi Junior Research Award (2016), Mellon Mentoring Award (2017), and Celebration of Engineering & Technology Innovation Award (CETI) in the Outstanding Early Career Researcher category from FIATECH (2018).
Burcin will explore data-driven disaster-prepared buildings while at the Turing. We see an increasing number of man-made and natural disasters striking our built infrastructure (e.g., building fires, acts of extreme violence, earthquakes). There is little insight in how people behave when exposed to these stressors; how behaviour is influenced by the building’s design, building type, person’s past experiences, people around them, people they are responsible for and so on.
Most theories and models assume behaviour is similar under different stressors. However, the impact on a building’s structure, physical conditions inside the building and the surrounding environment are distinct from one another in different emergency scenarios. Work to date used traditional methods, such as unannounced fire drills, post-surveys, video-recordings, and so on. However, these methods do not trigger natural responses (like trauma, panic, etc.), they lack realistic scenario features (fire, smoke, explosion) or do not provide opportunities for controlled experiments. On the other hand, we cannot expose people to unsafe conditions for moral and legal reasons. Thus, she proposes to study behaviour in different building conditions and under different extreme events using immersive virtual environments and agent based modelling.
The outcomes of this work will inform computational models that attempt to simulate emergency behaviour by predicting actions like evacuation, sheltering, decisions made during performing these actions, and the time it takes to take these actions more accurately. With more accurate data driven models, engineers and architects can develop safer and more secure building designs and operational procedures that are driven by empirical data.