Interim co-directors named for Integrative Data Science Initiative

Catherine Hill, professor of entomology, and Mark Daniel Ward, professor of statistics, have been named interim co-directors for the Integrative Data Science Initiative (IDSI), effective immediately.

Jay Akridge, provost and executive vice president for academic affairs and diversity, and Theresa Mayer, executive vice president for research and partnerships, announced the appointments.

“We look forward to working with Cate and Mark on the continued vision for data science at Purdue,” Mayer said. “They bring significant experience to the task given their prior roles with IDSI and will complement each other as we work to expand interdisciplinary research and teaching in data science across campus.”

Hill has been a President’s Fellow for the Life Sciences and an associate director for IDSI since 2018.

“Purdue leads in many areas of data science,” Hill said. “Our goal is to help our research and learning communities come together to drive nation-leading research, support innovative partnerships and further implement Purdue’s vision of an integrative data science ecosystem.”

Ward also has been an associate director for IDSI since 2018 and the director of The Data Mine at Purdue, a large-scale living learning community for undergraduates from all majors.

“I look forward to engaging even more closely with the Purdue community and our external partners,” he said. “We want to build new partnerships and also bolster the current research and education initiatives, across the full spectrum of the data sciences.”

Hill and Ward succeed David Ebert, Silicon Valley professor of electrical and computer engineering, who stepped down from his role as director this summer to become the associate vice president for research and partnerships, and Gallogly Chair in Engineering, at the University of Oklahoma.

The Integrative Data Science Initiative is designed to build on and advance Purdue's existing strengths to position the University as a leader at the forefront of data science-enabled research and education, by tightly coupling theory, discovery and applications while providing students with an integrated, data science-fluent campus ecosystem.