Lewis receives ASME Zwiep Innovation in Education Award

Kemper Lewis.

Kemper Lewis, Moog Professor of Innovation and chair of the Department of Mechanical and Aerospace Engineering. Photo credit: The Onion Studio.

By Sarah D'Iorio

Published May 6, 2019

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“We congratulate Kemper on this well-deserved award. He is a truly gifted educator who leverages his expertise in design and optimization to continuously improve the learning experience and outcomes for his students. ”
Liesl Folks, Dean
School of Engineering and Applied Sciences

Kemper Lewis, chair of the Department of Mechanical and Aerospace Engineering and Moog Professor of Innovation, is the recipient of the 2019 ASME Donald N. Zwiep Innovation in Education Award.

The award recognizes mechanical engineering programs for exceptional and innovative engagement in and fostering advances in mechanical engineering education, particularly those who have demonstrated exemplary contributions to the advancement of mechanical and multidisciplinary project-based engineering education.

“We congratulate Kemper on this well-deserved award. He is a truly gifted educator who leverages his expertise in design and optimization to continuously improve the learning experience and outcomes for his students. He also brings an infectious enthusiasm for the discipline into the classroom – our students can’t help but be drawn into the technical material that he teaches,” said Liesl Folks, dean of the School of Engineering and Applied Sciences.

Lewis is a renowned expert in design science, systems optimization, tradespace modeling, and machine learning in design, with a proven track record of productive collaboration with industry.

He is an ASME Fellow and Director of UB’s Community of Excellence in Sustainable Manufacturing and Advanced Robotic Technologies (SMART), an initiative that harnesses the strengths of faculty across the university to develop advanced manufacturing and design processes including autonomy, intelligence and materials technologies.

One of his current research projects, with previous funding from the National Science Foundation, focuses on cyber-empathic design, which leverages embedded product sensors in addition to other data sources to measure and predict a product’s effectiveness using machine learning in the ever-emerging Internet of Things.