Industrial engineering (IE) graduate student Saba Moeinizade did not know what to expect when the student poster competition for the INFORMS annual meeting was made virtual. She certainly was not expecting a podium finish, so she was pleasantly surprised when the judges awarded second place to her entry.
Her presentation – “A Simulation-based Optimization Approach for Improving Response in Multi-trait Genomic Selection” – was based off of a project she’s been working on with a team of interdisciplinary researchers at Iowa State University. The team proposed a simulation-based optimization approach for improving response in genomic selection while considering multiple characteristics, such as grain quality, yield, plant height and drought resistance.
“The motivation behind this work is to enhance efficiency of plant breeding programs by taking advantage of operations research methods,” said Moeinizade, a Ph.D. candidate in IE. “We want to find out how to optimize selection and mating decisions in a breeding program considering multiple traits of interest.”
The team’s proposed algorithm focuses on optimizing genetic gain with respect to a focal trait, such as yield, while controlling the variation in multiple secondary traits, like plant height. This research, which was published in the journal Genetics in August 2020, brought together researchers from not only Iowa State’s Department of Industrial and Manufacturing Systems Engineering (IMSE) but also the agronomy department.
Patrick S. Schnable, C.F. Curtiss Distinguished Professor in agronomy and Iowa Corn Endowed Chair in Genetics, and his graduate student Aaron Kusmec, contributed their expertise in genetics and plant breeding. IMSE associate professors Guiping Hu and Lizhi Wang provided expertise from an operations research and analytics perspective. Hu and Wang are also Moeinizade’s major professors.
“This collaboration has been an invaluable experience for me,” Moeinizade said.
Stochastic simulation and computational optimization were the main IE techniques Moeinizade applied to her parts of the project. She said courses like I E 534: Linear Programming and I E 634: Computational Optimization provided her with the foundation to apply these techniques to other projects.
“Actually, during my first year at Iowa State, I took these two courses and one of the course projects was a competition in genomic selection which later on led to the research interests that I am pursuing today,” she said.
Moeinizade completed her B.S. in IE from Amirkabir University of Technology in Iran’s capital city, prior to coming to Iowa State University. She said it was the faculty and research taking place that attracted her to the institution nearly halfway across the globe.
“What attracted me to this specific program were the interesting research areas that faculty work on and also knowing that the department provides opportunities for students to work close to industry leaders to solve challenging analytics and operations research problems,” she said, adding that she appreciates the opportunity to attend professional conferences in the field
Moeinizade plans to complete her studies in spring 2021. After graduation she hopes to work as a data scientist for a “fast-growing and data-oriented company.”