Using math to understand human behavior
- June 2, 2021
- Kirbi Joe, ’21 IMBS Ph.D., will be using her applied mathematical training to begin her career as a data scientist
When Kirbi Joe graduated from UCI with her bachelor’s in mathematics and dual minors in economics and computer science, she knew she wanted to pursue work in applied - rather than the pure study of – math.
She landed a job as a research assistant in the Color Cognition Lab at UCI run by Kimberly Jameson, Institute for Mathematical Behavioral Sciences project scientist, and Joe enjoyed the work so much that she ended up applying and being accepted into the IMBS graduate program.
“I think it's so interesting to do work that lives at the intersection of mathematics and the social sciences,” she says. “Coming from a math background, I would have never thought those methods could be used to study and draw inference about human behavior. I've since learned that quantitative techniques can reveal very unique and informed insights into social phenomena which would otherwise be impossible or extremely difficult to uncover.”
She’s spent most of her time researching the evolutionary properties and dynamics of color naming systems through the application of computational models (e.g. agent-based modeling, machine learning). She employed a variety of models on a specific color naming data set and used the model results to provide commentary on some of the existing theories within the field. Her thesis reported both evidence supporting existing claims as well as some novel findings which could potentially inform future scholarship about color categorization systems.
“In this digital age where we can collect massive amounts of data about people and their behavior, there is an increasing interest and need to make sense of potential patterns among these data,” she says. “Given the ever-growing capabilities of computers and tech, it is possible to employ computational methods to analyze these large behavioral data sets. My research helps demonstrate the usefulness of these models when applied to behavioral data and further explores the types of domains that can be studied using more quantitatively-based techniques.”
During her time as a grad student, she was supported by the Social Sciences Associate Dean and Christian Werner Fellowships, an IFREE Small Grant for Experimental Economics, and she was a Summer Research Fellow at the Santa Fe Institute. Her work resulted in four co-authored studies published in scientific journals. She’s now looking forward to starting her career as a data scientist at The MITRE Corporation where she will continue to build and apply mathematical and statistical models.