Bryan Goldsmith, assistant professor in the Department of Chemical Engineering, has received the 1938E award from the College of Engineering.
Considered one of the most prestigious awards given by the College, the 1938E is given to only one assistant professor in the College each year in recognition of exceptional mentorship, teaching and contribution to their department.
Previous 1938E award recipients include Chemical Engineering faculty Andrej Lenert and Suljo Linic. Lenert received the award in 2022, making Goldsmith the second consecutive 1938E award received by Chemical Engineering faculty.
”I am very grateful to receive the 1938E award. The amazing students at the University of Michigan CoE and my colleagues are a privilege to interact with and we always learn so much from each other,” Goldsmith said. “I dedicate this award to all my teachers and mentors who have continually inspired me throughout my life.”
Goldsmith’s teaching philosophy centers around project-based learning, active lecturing and inclusive teaching which has been effective as students overwhelmingly categorize his courses and teaching as excellent.
Since joining the department in 2017, Goldsmith has been dedicated to developing and teaching graduate and undergraduate data science and machine learning courses for engineering students, including a first-year introductory ENGIN-100 course about practical data science for engineers, and a multi-disciplinary elective on data science.
“I developed these graduate and first-year-level data science courses to fill a void for engineering students who are not computer scientists and want to learn data science and machine learning,” Goldsmith said.
Goldsmith serves as a faculty advisor to the American Institute of Chemical Engineers (AIChE) Student Chapter, a member of the department’s Advisory Council, and as a mentor for first generation engineering students.
“Mentorship is one of my favorite aspects of being a professor,” Goldsmith said. “My goals are to instill lifelong learning and critical thinking skills that my students will use throughout their careers.”
In his time at the University, Goldsmith has mentored two post-doctoral students, nine PhD candidates, four master’s students, and 19 undergraduate students.
Goldsmith’s research aims to discover catalysts to address major scientific challenges like air and water pollution that are caused by increasing demand for chemical production and energy generation. His lab works to combine quantum mechanical modeling, molecular simulation and machine learning to gain knowledge of these materials to aid execution of their mission to help design a sustainable future.