Leia Stirling honored with the 2025 Neil Van Eenam Memorial Undergraduate Teaching Award
This prestigious award recognizes faculty members who have demonstrated outstanding dedication to undergraduate education, mentorship and curriculum innovation.
The University of Michigan (U-M) Department of Industrial and Operations Engineering (IOE) is proud to announce Associate Professor Leia Stirling as the recipient of the 2025 Neil Van Eenam Memorial Undergraduate Teaching Award. This award recognizes faculty members who have demonstrated outstanding dedication to undergraduate education, mentorship and curriculum innovation.
“She inspires me to be a more dedicated student and a better engineer, and I hope to one day be even a fraction as impactful as she has been on me and the University of Michigan community,” said one of Stirling’s students.
Stirling’s impact in undergraduate education
Professor Stirling holds a joint appointment in the U-M IOE and Robotics departments, where she has been instrumental in shaping undergraduate education. As Associate Chair of Undergraduate Education for Robotics, she has played a key role in advancing curriculum development for the emerging program, ensuring that students receive a dynamic and forward-thinking education in the field.
She helped create engaging undergraduate courses such as ENGR 100-820: Exoskeleton Human Factors and ROB 204: Introduction to Human-Robot Systems, which introduce students to human-centered engineering design and the ethical considerations of robotics. Her innovative teaching methods were particularly evident during the COVID-19 pandemic when she mailed hands-on learning kits to students, enabling meaningful virtual participation.
At IOE, Stirling has made a lasting impact with her research and implementation of exoskeletons and human motion into courses she has created such as IOE 535: Quantifying Human Motion through Wearable Sensors. She has also adapted other courses such as IOE 265: Probability and Statistics for Engineers. To adapt IOE 265 she incorporated additional consideration of data thinking skills, including considering common biases and how they can emerge in datasets and data interpretation. Her commitment to fostering supportive and community-centered learning environments has resonated deeply with students.