![]() The eScience Institute maintains close ties with the three other WRF-funded institutes on campus: the Institute for Neuroengineering, the Institute for Protein Design, and the Clean Energy Institute. To date, seven faculty have been hired bridging eight departments on campus. With funding from the Washington Research Foundation (WRF) and the Provost’s office, the eScience Institute supports the joint appointment of transformational faculty who are innovators in developing and applying data science methodologies to advance their field of discovery. How does the eScience Institute interact with other Data Science activities at UW? The eScience Institute is led by Ed Lazowska (Founding Director) and Bill Howe (Associate Director), with guidance from a small Executive Committee and a larger Steering Committee comprised of distinguished researchers across a variety of fields. This summer, the Studio housed the 22 participants in our Data Science for Social Good research program for graduate students, undergraduate students, and socioeconomically disadvantaged high school students. Weekly campus-wide “data science office hours” are held in the Studio by the eScience Institute, UW Libraries, two different branches of UW-IT (the campus computing organization), the statistical consulting service of the Center For Statistics and the Social Sciences (CSSS), Amazon Web Services, and others. Seminars and working groups regularly convene in the two large meeting rooms that can be reserved. The WRF Data Science Studio is thriving! Data scientists, research scientists, postdoctoral fellows, and program staff base their activities here. What happens in the WRF Data Science Studio? As the WRF Data Science Studio is open to the public on weekdays from 9am-5pm, we also attract students and researchers from around campus to study, meet, and participate in our events. A cohort of 13 postdoctoral data science fellows use “hot desk” space with varying regularity. We have offices or desk space for our program managers, administrative support, and web and communications strategist, and a shared office used primarily by the Associate Director. We have dedicated desk space (and a dedicated meeting room) for our permanent staff of four full-time data scientists and four part-time research scientists. With reconfigurable furniture and layouts, the space is designed for flexibility - providing our permanent data scientist staff space for individual quiet work and our broader community space for small group meetings, seminars, and hands-on training events. ![]() The WRF Data Science Studio brings together eScience Data Scientists and researchers who reside in academic units spread across our large campus. The WRF Data Science Studio is designed around the principle that innovative data science is advanced at universities through the creation of high quality physical spaces that successfully cultivate the “water cooler” effect (a place for serendipitous interactions), raise the level of prestige for data science and scientists, and are adaptable to a range of activities that can promote research collaborations and learning. What is the role of the WRF Data Science Studio? The studio features a 360 degree view that includes some of Seattle’s iconic landmarks. The eScience Institute is located in the Washington Research Foundation Data Science Studio, on the 6th floor of the Physics/Astronomy Tower on the southwest corner of the University of Washington campus. Our goal is to advance the development and application of these techniques and technologies across the University of Washington, as well as nationally and internationally across all fields of discovery. Our research team consists of individuals with diverse backgrounds in the physical, life, and social sciences who have complementary expertise in advanced statistical and computational techniques such as data management, visualization, and machine learning. At the University of Washington eScience Institute, our mission is to engage researchers across disciplines in developing and applying advanced computational methods and tools to real world problems in data-intensive discovery. Rapid advances in technology are transforming nearly every field from “data-poor” to “data-rich.” The ability to extract knowledge from this abundance of data is the cornerstone of 21st century discovery.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |