New faculty bring expertise in manufacturing, systems, and AI
The Grado Department of Industrial and Systems Engineering welcomed four new faculty members in 2025, a reflection of the department’s strategic investment in high-demand fields where the need for expertise is rapidly expanding — from data-driven decision-making to advanced manufacturing systems. The new faculty will lead cutting-edge research, foster interdisciplinary partnerships, and equip students with the skills to thrive in an evolving engineering landscape.
“We’re thrilled to welcome these outstanding faculty to our team,” said Eileen Van Aken, professor and department head in ISE. “Our students will benefit from their perspectives, and their work will expand our capabilities in areas critical to the future of engineering and the success of our graduates.”
Alkim Avsar, assistant professor, systems engineering
Avsar comes to Virginia Tech from Arizona State University, where she was a postdoctoral researcher. She earned a Ph.D. in systems engineering from Stevens Institute of Technology. Avsar is part of the department’s management & systems engineering program area. She is currently teaching a graduate course in the fundamentals of systems engineering.
Avsar’s research explores how to improve efficiency in collaborative and cooperative systems by focusing on the role of social factors in engineering decision making. Her work integrates systems engineering, behavioral science, game theory, and human factors to study how outcomes in complex systems are shaped not only by technical design but also by the interplay of human decisions and interactions. She conducts interdisciplinary, mixed-methods research using behavioral experiments, agent-based modeling, and survey design, combined with insights from psychology, economics, management, and engineering design.
Eric Brubaker, assistant professor, systems engineering
Brubaker comes to Virginia Tech from NASA, where he served as a senior complex systems engineer, and holds a Ph.D. in mechanical engineering from Stanford University. He is part of the department’s management & systems engineering program and is currently teaching a course in AI for systems engineering.
Brubaker’s research develops theory and methods to design complex systems and better span disciplinary, organizational, cultural, and human-AI boundaries. Drawing from design science, systems engineering, organization studies, learning sciences, critical studies, human-computer interaction, and other transdisciplinary scholarship, his work addresses complex societal challenges like access to water, energy, transportation, and healthcare. His studies involve ethnographic fieldwork, mixed-methods, and quasi-experimental approaches in partnership with organizations and communities.
Kelsey Coleman, associate professor of practice and Learning Factory director
Coleman comes to Virginia Tech from the Eaton Corporation in Roanoke, Virginia, where she worked in a variety of engineering roles over the course of eight years. She graduated from the University of Pittsburgh with a bachelor’s degree in industrial engineering.
In her role, she manages company outreach activities, including recruiting external projects for the ISE capstone Senior Design program and managing workforce development and continuing professional education engagements. She also oversees the Learning Factory, the department’s instructional lab that provides hands-on experiential learning opportunities focused on advanced manufacturing technologies such as computer numerical control machining, additive manufacturing, collaborative robots, and digital factory systems.
Yuhao Zhong, assistant professor, manufacturing
Zhong joins Virginia Tech from Texas A&M University, where he earned his Ph.D. in industrial and systems engineering and served as a research associate for the Texas A&M Institute for Manufacturing Systems. He is part of the department’s manufacturing systems engineering program area and is currently teaching a course in manufacturing processes.
Zhong’s research advances data science methods to address fundamental challenges in quality, safety, and performance assurance within complex manufacturing processes and systems, while embracing scientific knowledge discovery and Industry 5.0’s human-centric paradigms. His work develops explainable AI and computer vision techniques to enhance manufacturing processes and outcomes, as well as to support safe, efficient integration of autonomous robots into collaborative industrial environments.
