Category: News

• Fellow Emily Fox receives presidential award

  

  By Robin Brooks Emily Fox, eScience Institute data science fellow, has won the 2017 Presidential Early Career Award for Scientists and Engineers. Fox, associate professor of statistics and of computer science and engineering, and Amazon Professor of Machine Learning, was nominated by the National Science Foundation “for her groundbreaking work in large-scale Bayesian modeling and computational approaches…

• Fellow Cecilia Aragon receives Fulbright Award

  

  By Robin Brooks Cecilia Aragon, professor of Human Centered Design & Engineering and an eScience Institute senior data science fellow, has been conferred the distinguished Fulbright Award. Dr. Aragon will travel to the Universidad Técnica Federico Santa María in Valparaiso, Chile, in 2018, where she will conduct research on human-centered data science and social media analysis with…

• Data Science for Social Good collaboration nets WSDOT funding

  

  By Robin Brooks A collaboration between two eScience Institute Data Science for Social Good (DSSG) project leads has resulted in a financial award which allows them to continue their work. Mark Hallenbeck, director of the Washington State Transportation Center, and Anat Caspi, director of the Taskar Center for Accessible Technology, both eScience fellows, answered questions submitted…

• eScience Institute co-sponsors human services workshop

  

  By Robin Brooks On January 17 – 18, leaders and innovators from academic and governmental backgrounds will gather at the MetroLab Workshop on Big Data and Human Services to discuss common challenges and propose collaborative, data-driven solutions to human service issues. The workshop, co-sponsored by the eScience Institute, Urban@UW, the MetroLab Network, the City of…

• 2017 Data Science Career Fair

  

  The 2017 UW Data Science Career Fair will be held on Monday, October 23 from noon to 5 p.m. in the HUB Ballroom. Multiple UW departments and programs are working together to create this opportunity for undergraduates, graduate students, and postdocs working in data science to connect with companies and research labs looking for permanent…

• eScience Institute 2016 highlights

  

  By Robin Brooks As 2016 draws to a close, we wanted to take a moment to share some of the exciting milestones the eScience Institute hit over the course of the past year. Over 2400 attendees participated in hundreds of data science events, trainings, seminars, working groups and receptions from Nov. 1, 2015 through Oct.…

• Fellow collaborates on genome sequencing using cloud

  

    By Robin Brooks eScience Data Science Fellow Rob Fatland is featured in a story on the UW Information Technology website. Fatland, UW director of cloud and data solutions, helped graduate student Timothy Durham to reduce the time spent processing his genome sequencing data, and also assisted in freeing up Durham’s department’s server resources as well. More…

• Jake VanderPlas publishes Python handbook

  

  By Robin Brooks A new book by Jake VanderPlas, eScience Insitute’s director of research in physical sciences, was published in Nov. 2016 by O’Reilly Media. The Python Data Science Handbook is a detailed guide to the most important Python tools for data science, covering IPython, Jupyter, NumPy, Pandas, Matplotlib, Scikit-Learn, and other tools. Along with its free companion project, A…

• First Geohackweek held at eScience Institute

  

  By Robin Brooks The University of Washington’s eScience Institute hosted its first Geohackweek Nov. 14 – 18, 2016. Inspired by AstroHackWeek and Neurohackweek, the conference combined tutorials with group work (“hacks”) on computational projects in geospatial sciences. With the help of 15 instructors, the event offered training in open-source vector and raster processing, multidimensional array analysis, data visualization, remote…

• eScience fellows release new music dataset

  

  By Robin Brooks Sham Kakade, senior data science fellow, and Zaid Harchaoui, data science fellow, are part of a UW team that has developed MusicNet, a “classical music dataset … which enables machine learning algorithms to learn the features of classical music from scratch.” According to a UW press release, “MusicNet is the first publicly available large-scale…