Two faculty members in the College of Liberal Arts and Sciences were awarded named faculty positions thanks to a generous donation from Kingland and its owners, David and Deb Kingland.
Hridesh Rajan, professor in the Department of Computer Science, was named Kingland Professor of Data Analytics. Stephen Vardeman, University Professor in the Department of Statistics and the Department of Industrial and Manufacturing Systems Engineering, was named Kingland Data Analytics Faculty Fellow.
Rajan is the director of the Laboratory for Software Design in the Department of Computer Science at Iowa State. Through invention and refinement of shared cyberinfrastructures for data-driven sciences, Rajan's research on the Boa project, a software language and infrastructure that makes data mining easier, is decreasing the barrier to entry in data-driven science. He founded the Midwest Big Data Summer School to deliver broadly accessible data science curricula and serves as a Steering Committee member of the Midwest Big Data Hub (MBDH).
He received a National Science Foundation (NSF) CAREER award in 2009, LAS Early Achievement in Research Award in 2010, a Big-12 Fellowship in 2012, and an Association for Computing Machinery (ACM) Senior Membership in 2014. His recent work includes co-leading efforts to establish three new educational programs in data science at ISU.
The funds will support his research in investigating shared infrastructures for data driven science giving researchers easy access to big data analysis that would otherwise require specialized computation expertise, datasets, and infrastructure they may not have access to.
"This Kingland award will have a strong positive impact in that it will open new doors for me,” he said. “The support will allow me to reach out and visit a broader set of agencies and foundations to tell them about the research and education programs in data science at Iowa State University, and to seek their feedback."
Vardeman is the winner of the 1994 American Society for Engineering Education (ASEE) Meriam-Wiley Distinguished Author Award for an outstanding new engineering textbook (Statistics for Engineering Problem Solving). He has also coauthored three additional statistic textbooks, and is a Fellow of the American Statistical Association and Elected Member of the International Statistical Institute. From 1993 through 1995 he edited Technometrics, the world's leading journal of statistics for the engineering and physical sciences. Since joining the Iowa State faculty in 1981, he has advised or co-advised 28 Ph.D. and 52 M.S. students to completion, most recent ones with machine learning research topics.
Vardeman’s research interests span many areas in statistics. For the last decade he has been particularly interested in data analytics and statistical machine learning. These methods are used to find and quantify patterns or relationships in datasets large enough to require computer implementation. As “big data” grows, these methods are important in many applications such as identifying potential efficiency improvements in manufacturing plants, assessing the likelihood of an individual developing a medical condition based on patient records, applications in voter and marketing analytics, and more.
“I am grateful to the Kinglands for their generosity and kind support of basic research at Iowa State University,” Vardeman said. “The Kingland fellowship will provide flexibility and opportunities to myself and my graduate students that will be a real aid in moving the fundamentals of statistical machine learning forward.”
The awards are part of a $1.5 million donation to the College of Liberal Arts and Sciences, the College of Business, and the College of Engineering by Kingland, a global leader in data quality control, development and risk management, and from a personal donation by its owners, David and Deb Kingland, to support several areas in data science. The donation also established the Kingland Data Analytics Scholarship Fund, which will help attract top students and make the opportunity for a degree in data programs available to more students.
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