Mou selected as Outstanding Faculty Mentor

Shaoshuai Mou, an assistant professor in AAE, was recognized for his outstanding work mentoring master’s and Ph.D. students.
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(From left) Tom Shih, J. William Uhrig and Anastasia Vournas Head and Professor of Aeronautics and Astronautics; James Peck, Aero Assist; Shaoshuai Mou; Wayne Chen, Reilly Professor of Aeronautics and Astronautics & Materials Engineering and Aeronautics and Astronautics Associate Head for Graduate Education. 

Shaoshuai Mou, an assistant professor in AAE, has been selected as the Outstanding Faculty Mentor of Engineering Graduate Students.

The award is presented annually by the College of Engineering to an individual faculty member in each School of Engineering to recognize outstanding work mentoring master’s and Ph.D. students. Aero Assist, the graduate student organization in AAE, received several nominations. The group was “most impressed by what our colleagues had to say about Dr. Mou” and sent that nomination to the College.

Mou teaches AAE590, Distributed Network Control, which prepares graduate students with a solid background for multi-agent networks and offers an introduction to frontier topics in autonomy. In the past three years, he has served as the thesis committee chair (or member) for supervising more than 20 graduate students from AAE, ECE, Civil, and IE, across the College.

“This award is a big surprise, and also a significant encouragement to me, especially considering the nomination and selection are purely made by students,” Mou says. “I am proud of being a faculty member here at Purdue since we have so many excellent students. Our students are also my mentors, and I have learned a lot from them, especially their passion on research, eagerness for knowledge, and hard work for their future success.”

Mou, who joined Purdue in 2015, leads the Autonomous & Intelligent Multi-Agent Systems Lab. The group aims to investigate autonomy and intelligence for networked systems consisting of multiple unmanned mobile agents, through combination of theories in control, networks, optimizations and artificial intelligence.