USU Statistics Doctoral Student Tackles 'Big Data,' Attends Global Forum

Are we drowning in information? Sometimes, it feels like it. But Utah State University statistician Brennan Bean says “big data,” the term given to massive volumes of information, can help us find solutions to many challenges and make more informed decisions, if we explore and refine ways to harness, analyze and distill it.

A doctoral student, Bean gathered with fellow information specialists April 8-11, for SAS Global Forum 2018 in Denver, a conference hosted by the Cary, North Carolina-based global data analytics firm, to discuss the latest ideas and tools for statistical analysis.

“It was an amazing experience,” says the Rexburg, Idaho native, who proudly describes himself as a fourth-generation Aggie. “We heard from leaders in the field about a wide range of topics, including advances in artificial intelligence, using predictive analytics to forecast the opioid crisis and using iPhones to monitor endangered species.”

Bean’s participation in the forum stemmed from his selection as a 2017 Summer Statistics Fellow at the SAS Institute in North Carolina.

“Professor Richard Cutler and my advisor, Yan Sun, both faculty members in USU’s Department of Mathematics and Statistics, introduced me to this opportunity,” he says. “SAS offered only two PhD fellowships in the SAS/STAT group that summer and I am confident I would never have been able to successfully pursue this opportunity without guidance from my mentors at Utah State.”

Prior to the internship, Bean says he envisioned a future career in academia, but the SAS experience gave him a glimpse of corporate opportunities.

“My duties included software development testing,” he says. “I had great mentors. Everyone was very supportive and patient, as I climbed a steep learning curve.”

At USU, Bean, who serves as president of the USU Data Analytics Club, student chapter of the American Statistical Association, is developing new spatial statistical models, along with associated algorithms, for handling measurement uncertainty.

“For example, these models could be applied to study of climate questions, where measurements are uncertain,” he says. “Instead of trying to apply statistics meant for single values in space, we can apply models to a range of data – intervals in space.”

Bean is the primary researcher for the Utah Snow Load Study, a project he’s conducting with Sun and USU faculty researcher Marc Maguire of the Department of Civil and Environmental Engineering. The project, which will culminate in an updated set of ground snow load requirements for safe building design, will become part of Utah state law.”

“USU’s statistics program is small, but is very cutting edge,” he says. “I feel like I stumbled on a really great secret.”

At SAS, Bean worked alongside students and graduates of larger, more well-known academic programs, but says he never felt at a disadvantage.

“I was definitely prepared for the challenges,” he says. “That gave me a lot of confidence and made me realize there are great opportunities for the skill set of a doctoral-level statistician. The door is wide open.”

Contact: Brennan Bean, brennan.bean20@gmail.com
Writer: Mary-Ann Muffoletto, 435-797-3517, maryann.muffoletto@usu.edu