Rosen uses computational methods rooted in quantum mechanics to design new materials that can address global challenges in energy and sustainability. He is most interested in narrowing the divide between theory and experiments by using artificial intelligence to address key questions regarding the synthesis, characterization and performance of new materials for clean energy technologies.

“Compared to the weeks or months it may take to test a single material in the lab, it has recently become possible to study thousands of materials — in parallel — on the computer in just a matter of days,” he said. “And the scale of materials science problems that we can tackle is growing rapidly due in large part to significant advances in machine learning.”

Rosen looks for ways to make computational materials design more actionable for those doing experiments. He said that a lot of work has been done to design theoretical materials with promising properties but that there remain many important challenges in translating such advances into ones that meaningfully impact society. But if computational methods can better capture the inherent complexities of real materials studied by researchers in the lab, then it will become easier to identify those materials that are not only interesting or exotic but also viable.

“My hope is that students are interested in this computational way of thinking. That we can use computation as a complimentary tool to guide experiments,” he said. “I want everything we do to have very close ties with an experiment that could be done.” 

He also emphasized that computational science can be applied to many different application areas, something he wants students to leverage within the core expertise of his group.

A Long Island native, Rosen earned his undergraduate degree in chemical engineering from Tufts University before completing a Ph.D. at Northwestern University in 2021. His first research experience was through a sponsored by the Princeton Plasma Physics Laboratory. Since then, Rosen has received a Goldwater Scholarship, a National Defense Science and Engineering Graduate Fellowship, a Presidential Fellowship from Northwestern, and a Miller Research Fellowship from the University of California-Berkeley, where he was a postdoc. 

Rosen is an associated faculty member of the Princeton Materials Institute, the Princeton Institute for Computational Science and Engineering and the Center for Statistics and Machine Learning.