Image of Business Instructional Facility

Nov 5, 2021 2021-11 Accountancy Faculty

New DSRS director offers Gies researchers the moon and the stars

On paper, Matias Carrasco Kind isn’t your typical business school recruit. He’s not a finance expert or a supply chain guru. Or someone leaving a Big Four job for a second career in academia. But as an astrophysicist he does understand big data and artificial intelligence, and that makes him an invaluable asset to a school reinforcing its analytics program as one of the best in the world.

For Carrasco Kind, the journey to Gies started more than a decade ago, when he first arrived at the University of Illinois. Originally from Chile, he and his wife, Andrea, were looking for a family-friendly community to raise their son while he completed his graduate degree. After earning both a master’s and a PhD in his chosen field — and welcoming two more kids, he joined the National Center for Supercomputing Applications as a research scientist. And that’s probably where he would have stayed, if it weren’t for a conversation with Robert Brunner, associate dean for innovation and chief disruption officer at Gies.

Brunner, who is also affiliated with the Department of Astronomy and NSCA, was working on a novel idea at the time. He wanted to create a new research service at Gies that would help business faculty better leverage big data, machine learning and data science methods in their work. The idea intrigued Carrasco Kind, who was used to working with vast amounts of complex data.

“Even though my research was focusing in astrophysics, everything required to do that research involved advanced data science techniques,” said Carrasco Kind. “And I quickly realized that I could apply all those methods and techniques to any field.”

When the Data Science Research Service (DSRS) officially opened its doors, Carrasco Kind signed on as assistant director, helping shape a program that drives research at Gies by assisting students, faculty, and staff with their data science needs. This summer, he officially dropped the “assistant” part of his title, joining Gies full-time in order to guide a popular service that’s growing by leaps and bounds.

This last year alone, DSRS helped over 20 faculty across all the departments at Gies — and a couple from other colleges as well, providing their data science consulting, statistical analysis, and cloud computing resources. Among other things, they helped faculty develop deep-learning models to forecast urban mobility patterns, scrape data from the web, create dashboards and provided Jupyter environments to analyze credit card user datasets.

“It's been a great learning experience,” said Carrasco Kind, who enjoys collaborating with a wide range of departments and believes that collaboration provides a tremendous benefit to Gies. “Usually in colleges like this, people tend to work isolated in their own environment, but because I’m learning about research from different areas, I can say, ‘I know a professor working on this and a professor working on that. Maybe we can do it all together.’ So we don’t just assist people. We serve as a bridge-point for research.”

It’s not just people that he’s bringing together. Carrasco Kind hopes to make the service a hub for data at Gies, hosting the vast datasets the College is acquiring and facilitating its use.

Now fulltime with Gies as a Research Professor, he will also be teaching data-related courses and transitioning his personal research to focus on issues related to the business world. He has already improved an existing and popular machine learning technique to find patterns and outliers in large datasets, creating a useful tool that’s widely used across many different disciplines.

“There’s so much data out there, especially in business areas like finance and marketing,” said Carrasco Kind. “We need to leverage that big data and new techniques to help researchers up their game.” And he believes the Data Science Research Service is well positioned to do that, transforming one of the world’s top business schools into a recognized center for high-class, data-driven research.