The National Science Foundation (NSF) has awarded Civil and Environmental Engineering Assistant Professor Matteo Pozzi the NSF Faculty Early Career Development (CAREER) Award, a prestigious five-year grant given to junior faculty for research and education.

Pozzi’s research focuses on the potential of sensors and robotic technology to collect data that can inform decision-making. Through integrating models and probabilistic computational approaches, Pozzi hopes to not only optimize infrastructure operation and maintenance, but also the continued collection of information.

“Because we are managing such limited resources, data collection, this process of learning about the infrastructure, must be optimized,” he explains, proposing that algorithms could offer guidance on where and when to add more sensors, schedule inspections, or conduct strategic testing.

Because we are managing such limited resources, data collection must be optimized.

Matteo Pozzi, Assistant Professor, CEE, Carnegie Mellon University

“Managers also have to compare the benefits of collecting information with the benefits of repairing various components, where each choice is expensive,” he adds. “This is what I am trying to develop—approaches and algorithms to make these comparisons and to suggest strategies that are optimal both for collecting information and for taking actions to benefit a component.”

As Pozzi establishes and refines his algorithms, he will also develop methods to teach infrastructure planning and analysis. Partnering with CMU’s Summer Engineering Experience for Girls program, Pozzi plans to build a simulation game in which students act as virtual infrastructure managers who must develop, test, and revise decision-making strategies in the face of persistent risk and uncertainty.

“I'm excited because it's an expansive, long-term project that allows me to investigate topics I am passionate about, to educate students, and to form a path in the direction in which I want to research and teach.”