Junior Faculty Teaching Fellow Spotlight:Bennett Landman
Each month, the CFT Newsletter highlights the work of our Junior Faculty Teaching Fellows. This month, Bennett Landman, Assistant Professor, Electrical Engineering & Computer Science, talks about his teaching philosophy and interests:
The opportunity to work with, teach and learn from creative young individuals is one of the great privileges of being a faculty member. For the past two years, I have taught undergraduate signal processing and graduate medical imaging courses in Electrical Engineering. Each class has been a unique and rewarding experience which led me to update the class material after every semester. One of the primary challenges that I have faced is conveying enthusiasm and imparting excitement about subject matter that is mathematically abstract and demanding. I see the Junior Faculty Teaching Fellowship Program as natural evolution of my engagement with the Center for Teaching. I am eager to engage in inter-disciplinary discussion of pedantic methods and learn more about what works in difficult/interesting classroom situations. I see my strengths as being passionate and knowledgeable about the subject material (especially in individual/small group settings), but I feel that I have ample room for improvement in terms of organizing classroom flow (engagement with larger groups, sparking interest in mathematical derivations).
“Each class has been a unique and rewarding experience which led me to update the class material after every semester. One of the primary challenges that I have faced is conveying enthusiasm and imparting excitement about subject matter that is mathematically abstract and demanding.”
My research lies at the interface of medical imaging, signal processing, and statistical inference. Students are often surprised to find me in Electrical Engineering, as my projects range from understanding the neurological basis of psychological disorders and mapping brain tumors to statistical method development and visualizing abdominal defects. The common theme that unifies my work is capturing quantitative information from three-(or higher) dimensional medical images. Over the past few decades, physicists have created marvelous tools to peer inside living people; we are just at the threshold where, as engineers, we can create systems to help unravel these data. The signal processing and information fundamentals in the undergraduate curriculum have broad applications throughout modern engineering. I consider it a personal challenge to provide students with essential concepts and tools that can carry forward into their careers.
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