College of Engineering News • Iowa State University

IMSE’s Li brings statistical focus to the department


One of industrial and manufacturing systems engineering’s (IMSE) newest faculty members has brought her statistical expertise with her to Ames.

Qing Li joined the IMSE faculty as an assistant professor in fall 2018. Prior to coming to Iowa State, she served as a visiting assistant professor of statistics at the University of Wisconsin-Madison.

Li holds a Ph.D. and M.S. in statistics from Virginia Tech University. She also has a M.S. in electrical engineering from the University of Rochester in New York and a B.S. in information and electronics information from Tsinghua University in Beijing, China.

Li’s unique skill set combines elements of statistics and computer science with civil, electrical and industrial engineering. At Iowa State her research will focus on Bayesian hierarchical modeling, recurrent-event change-point detection, clustering and statistical analysis in engineering applications.

“Data is available for these real problems,” said Li. “I am especially interested in making data-driven decisions to generate real-world benefits and plan to collaborate with other researchers in engineering.”

Li teaches I E 361: Statistical Quality Assurance in Physics Hall on August 28, 2018.

This fall she is teaching I E 361: Statistical Quality Assurance which covers statistical methods for process improvement and other ways in which statistics can be applied to the field of industrial engineering.

“Statistics and industrial engineering are closely interrelated,” said Li. “What measurements should be taken to monitor the manufacturing process, how to collect data and how to analyze the data to make decisions that will improve the process are in the realm of statistics. These are some of the things I plan to study.”

Li teaches I E 361: Statistical Quality Assurance in Physics Hall on August 28, 2018.

Outside of work, Li enjoys listening to classical music – particularly masterpieces by Mozart and Beethoven – and also likes to spend time with her family.

“I find reasonable time management very helpful in living a balanced life. I try to assign a task for each time block and focus on one task at a time. For example, Saturday morning is the time with family, and I will not worry about work. Monday morning is the time to prepare for teaching, and I will not worry about research.”