The University of Illinois announced recently that statistics professor Naveen Narisetty has been awarded a grant by the National Science Foundation.
Narisetty received a distinguished Faculty Early Career Development Program Award that will support his work in exploring several key aspects of big data and how statisticians and data scientists can more efficiently work within the Bayesian framework for real world application, the university said.
The CAREER Program is the NSF’s most prestigious award in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization.
Narisetty's five-year agenda to create more efficiency within the big data framework has the potential to influence multiple disciplines including biology, economics, environmental sciences, marketing, and medical sciences. The research will be integrated into teaching special topics courses for graduate and undergraduate students and developing an outreach workshop for K-12 students to provide exposure to modern statistics and its applications.
The most impressive note of the Indian American researcher’s work may be its diverse applicability. He has made site visits to pharmaceutical companies and within the banking industry to better understand the different challenges that could be met with the same process, it said.
Both industries have access to an incredible amount of heterogeneous data but need to access answers from this data in real time, the university adds.
“These techniques can be used to evaluate the performance of a specific drug and make the correct dosage levels, while, in the banking context, they’re trying to use the same statistical techniques to answer very different questions with what factors are influencing a borrower to default on a loan,” Narisetty said in the release.
Narisetty’s initial exploration of the Bayesian framework during his years as a Ph.D. student was mainly regarding its theoretical aspects. Now, he’s evolved his research to consider how the application can be utilized in real life, according to the report.
“I realized ultimately the purpose of any of this complex statistical machinery that we are developing is to translate it into good practice and to benefit society,” he adds.
“I feel that a lot of times, questions that we ask appear interesting, but I feel just being interesting is not sufficient. Having a larger purpose of serving society and having immediate application is more important than just being interesting,” he said.