Establishing Data Science Thought Leaders

The Northwestern Mutual Data Science Institute is committed to solving important business and community challenges by harnessing the power of data for research and scientific discovery.

Our research efforts are prioritized by using data to address three major themes:

  • Tackling some of the world’s largest health crises
  • Addressing challenging social issues that affect a large population
  • Finding innovative solutions for business and industry problems

Underlying these areas is an unwavering focus on the ethical use of data to ensure we’re on the cutting edge of data science trends and effecting positive change in a responsible manner.


NMDSI Active Research

NMDSI-supported research advances innovative ideas, while fostering collaborations that will lead to long-term, deep relationships among faculty — across disciplines — at both UW-Milwaukee and Marquette. Through these collaborations, we will maximize contributions to data science while producing internationally-recognized data science research and thought leadership. Check out these current active projects:

The Elecurator Project

The project tracks the major issues engaging both candidates and voters in the 2020 presidential election cycle. Using a technique known as social curation, the team is analyzing multiple sources of data to see what topics are important to voters and how the candidates are speaking about those same issues.

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Meet our Researchers

  • Daniel B. Rowe, Ph.D
  • Elected ASA Fellow
  • Professor of Computational Mathematical and Statistical Sciences
  • Director of Applied Statistics Master's Program
  • Director of Graduate Studies for Mathematical and Statistical Sciences
  • Marquette University

Dr. Daniel B. Rowe has conducted research in advanced brain image modeling and analysis and his work in the determination of active brain areas using functional magnetic resonance imaging (FMRI) has been published extensively.

When asked about the aspects of his work that he is most proud of, Rowe said, “The original measurements in MRI and FMRI are truly complex-valued (imaginary numbers with real and imaginary parts). I have been utilizing this fact to gain a statistical advantage over the standard practice of using the magnitude-only data. The methodological innovations from my research demonstrate that new methodology can be developed to create a new model to describe a physical process instead of applying existing methodology in different ways.” He hopes that his research legacy will be that neuroscientists will utilize the full complex-valued images for determination of active voxels in FMRI brain imaging.

If he was able to collaborate with any other scientist (across disciplines, living or deceased), Dr. Rowe would choose Richard Feynman. “I would like to sit around a campfire listening to him play the bongos and tell safecracking stories from his days working on the Manhattan Project.”

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Affiliated Faculty

The NMDSI Affiliated Faculty program provides resources and support to data science faculty, tracks data science research and education, and facilitates building expert multidisciplinary teams from faculty with overlapping or complementary skills and interests.

By building a data science community based on collaboration and increasing the collective impact of data science research, the NMDSI Affiliated Faculty program brings us one step closer to achieving our goal of transforming our world through the power of data science.

Interested in joining the NMDSI Affiliated Faculty program? Submit your application below.

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