School of Education News

Rau, Matthews, Kaplan part of interdisciplinary UW team landing $3M NSF grant

September 21, 2015

The School of Education’s Martina Rau, Percival Matthews and David Kaplan are all part of a uniquely diverse team of faculty members from across the UW-Madison campus that was recently awarded a $3 million graduate training grant from the National Science Foundation.

This interdisciplinary program in learning, understanding, cognition, intelligence and data science is called LUCID. The initiative will support graduate students working on interdisciplinary projects that focus on translating theories of learning into technological innovations. Students in this program will go through a personalized curriculum featuring many opportunities for cross-disciplinary training, junior trainee mentoring, internships, seminar series and summer retreats. 

Martina Rau
Rau
“Solving today's problems requires an interdisciplinary perspective,” says Rau, one of LUCID’s co-investigators who is an assistant professor with the nation’s No. 1-ranked Department of Educational Psychology. “The grant will allow us to prepare a new generation of interdisciplinary scholars who have a strong footing in their home discipline, but who are also experienced in working in collaborative teams to develop and apply state of the art data science approaches to problems at the intersection of human cognition, machine learning, and education.” 

The LUCID team is being led by principal investigator Tim Rogers, a professor with the Department of Psychology. In addition to Rau, other co-investigators include: Jerry Zhu, associate professor, Department of Computer Sciences; Rob Nowak, professor, Department of Electrical and Computer Engineering.

Other core UW-Madison faculty involved with the grant include the Department of Educational Psychology’s Matthews and Kaplan, and the Department of Electrical and Computer Engineering’s Bilge Mutlu and Rebecca Willett.

The grant proposal explains that LUCID will train students in the collaborative pursuit of data-enabled research at the intersection of human and machine learning and teaching. The initiative will allow about 40 graduate trainees from the Departments of Engineering, Computer Sciences, Psychology and Educational Psychology to work collaboratively on central problems, concepts and applications relevant to understanding learning, teaching, cognition and behavior in humans and machines.

The LUCID project will train young scientists to advance basic and applied research in domains where machines are used to instruct, predict, understand, respond to or learn from human users.

This cross-disciplinary project will allow for a range of diverse expertise that is hard to acquire through traditional channels, since the core areas of study are traditionally segregated. Through this process, LUCID aims to provide the graduate students with sufficient knowledge and experience to collaborate effectively in cross-disciplinary partnerships.


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