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Professor Parag Banerjee has been notably recognized and named a fellow of the American Vacuum Society.

Through his pioneering work regarding the discipline of vacuum science in atomic layer deposition (ALD) and surface engineering, Banerjee is honored to be acknowledged for this fellowship.

“Being named to the 2026 class of AVS Fellows is an incredibly meaningful recognition, both personally and for the trajectory of my research program,” he says. “It is also a moment to reflect on the mentors, students and collaborators who have shaped this work, and it motivates me to keep pushing the boundaries of what atomically precise materials synthesis can enable.”

Banerjee and his team are in the process of developing new etching strategies that allow them to engineer surfaces and apply them to catalysis and solar energy harvesting. But what Banerjee says he’s most proud of is how far his team has come since he started at UCF in 2018.

“I’m equally proud of building an interdisciplinary research culture,” he says. “Leading UCF’s Renewable Energy and Chemical Transformation (REACT) faculty cluster has let us connect materials synthesis expertise with colleagues across chemistry, physics, and engineering to tackle energy and sustainability problems that no single lab could address alone.”

However, he holds the most esteem for his diligent mentees.

“Beyond the lab, training the undergraduate and graduate students who have come through my group – several of whom have gone on to careers in the semiconductor industry and academia – is the work I’m proudest of overall.”

About the Researcher

Banerjee is a professor in the UCF Department of Materials Science and Engineering. He earned his Ph.D. in Materials Science and Engineering from the University of Maryland, College Park. Prior to joining UCF in 2018, he was an assistant professor at Washington University in St. Louis, and before entering academia, he spent six years as a research and development process engineer at Micron Technology, developing high-k dielectric materials for memory applications.

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