DeFord receives University of Chicago Outstanding Educator Award

Data Analytics Assistant Professor Daryl DeFord recently received the University of Chicago Outstanding Educator Award for his work mentoring a local high school student.

Each year, newly admitted UChicago students have the opportunity to reflect on their time in K-12 and nominate an educator who played a significant role in their education. The student nominated DeFord for the Outstanding Educator Award for his work mentoring him from 2022-2024.

"Knowing that my effort had a significant positive impact on his education and academic journey is extremely gratifying, and I really enjoy getting to see students develop as researchers and move on to new opportunities and experiences," DeFord said.

One of DeFord's favorite parts of being a professor is getting to mentor student researchers. During his time at WSU, he has enjoyed the opportunity to collaborate with students at all levels-from high school through PhD.

"Students in my lab work on a wide variety of topics in mathematics, statistics, and data analysis, often motivated by applications to data from the social sciences," he said. "These interdisciplinary projects provide natural starting points for junior researchers to engage with the entire research process, and it is always exciting to see them make new discoveries and develop as scholars."

DeFord will join other faculty awardees to be honored in a virtual event later this month to recognize his excellence in teaching and serving as a role model for all his students.

DeFord is an assistant professor of data analytics in the Department of Mathematics and Statistics. He earned his undergraduate degree from the math department at WSU and developed an interest in research as a junior and senior working on projects supervised by faculty members in math and computer science. During his PhD work at Dartmouth and postdoc at MIT, he worked on mathematical models for analysis of social data.

Most recently, his work has focused on building tools for detecting and combating gerrymandering of political districts, including consulting on redistricting lawsuits and writing amicus briefs. Additionally, he teaches students about mathematical approaches to data analysis, as well as conducting similar work with organizations, such as the Metric Geometry and Gerrymandering Group, Voting Rights Data Institute, and Data Science for Social Good program.