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The National Science Foundation announced on Sept. 11 that it is awarding grants totaling $8.5 million to 19 collaborative projects at 23 universities for the study of complex and entrenched problems in data science. Three of these projects will be based at the University of Washington and led by researchers in the College of Engineering and the College of Arts & Sciences.
The grants build on 2017 awards in the Transdisciplinary Research in Principles of Data - or TRIPODS - program. These new grants make up the TRIPODS+X program, which expands these big-data projects into broader areas of science, engineering and mathematics. The lead faculty on these new projects are among the core founding faculty of the Algorithmic Foundations of Data Science Institute , the UW’s TRIPODS institute.
"The multidisciplinary approach for addressing the increasing volume and complexity of data enabled through the TRIPODS+X projects will have a profound impact on the field of data science and its use,” said Jim Kurose, NSF assistant director for Computer and Information Science and Engineering. "This impact will be sure to grow as data continues to drive scientific discovery and innovation.”
The TRIPODS program’s convergent and interdisciplinary approach emerged from the 2016 NSF TRIPODS workshop. Since then, the program has evolved into a community of institutes that share expertise and work together to advance the three NSF priorities central to TRIPODS: research, visioning and education. Research-track projects aim to develop new algorithms and fundamental approaches to data-driven challenges. Visioning projects focus on fostering collaboration across disciplines and help spawn well-integrated research teams that yield truly new perspectives. Education projects are pilot efforts that aim to drive workforce development in multiple disciplines and at multiple education levels. Each TRIPODS institute will have three years to use its award to expand efforts in one of these program tracks.
The first UW-led project, a research-track endeavor, is called "Safe Imitation Learning for Robotics” and is led by assistant professor of statistics and eScience Institute fellow Zaid Harchaoui. This project will focus on imitation learning in robotics, a form of learning in which a system learns through demonstration. Researchers will design trust-building learning algorithms and lay the groundwork for safe imitation-learning approaches for beneficial human-machine interaction. Additional UW researchers on this project include associate professor of electrical engineering Maryam Fazel ; Sham Kakade , an associate professor in both the Department of Statistics and the Paul G. Allen School of Computer Science & Engineering; and Sidd Srinivasa , who is also a professor in the Allen School.
Fazel will lead the second TRIPODS+X project at the UW: "Foundational Training in Neuroscience and Geoscience via Hack Weeks.” This project will enhance the successful "hack week” model as a tool for data science education and collaboration. Hack weeks blend elements of traditional lecture-style pedagogy and participant-driven projects. Two hack week formats, one for neuroscience and one for the geosciences, have already been organized and held by researchers at the eScience Institute. For this project, hack week leaders will work to incorporate training on core methods in statistics and optimization in order to promote a deeper understanding of methodologies along with hands-on experience with data-driven problems in the geosciences and in neuroscience. Additional UW researchers on this project are Ariel Rokem at the eScience Institute; Anthony Arendt at the Applied Physics Laboratory; Aleksandr Aravkin , an assistant professor of applied mathematics; and Harchaoui.
The third UW-led TRIPODS+X project, "Scaling Up Descriptive Epidemiology and Metabolic Network Models via Faster Sampling,” is led by Yin Tat Lee , an assistant professor in the Allen School. This research track will focus on developing and disseminating practical analysis tools for public health and biological studies that involve large datasets and rely on accurate "sampling” - a principle of randomly drawing a subset of cases in a larger dataset, in order to identify trends quickly and speed up analysis. To develop these tools, this project will evaluate current big-data projects in health metrics and systems biology. Additional researchers on this project are Abraham Flaxman , an associate professor in the UW’s Institute for Health Metrics and Evaluation and Santosh Vempala , a professor of computing at Georgia Tech.
"TRIPODS+X is exciting not only for its near-term impact addressing some of society’s most important scientific challenges, but because of its potential for developing tools for future applications,” said Anne Kinney, NSF assistant director for Mathematical and Physical Sciences.