Last month the eScience Institute held the “Learning and Doing Data For Good” conference, an event for current students and alumni in university-based data for good programs, their project partners, and data science professionals. The goal was to inspire discussions and networking with others who are motivated to learn from and meet the needs of communities and people using data for change. The eScience Institute co-hosted the conference with the West Big Data Innovation Hub, the Academic Data Science Alliance, and the University of British Columbia’s Data Science Institute.
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The eScience Institute co-hosted Discovering AI@UW, an event that brought together artificial intelligence experts from across the University of Washington campus to discuss their projects and how they intersect. Over 180 people attended the event, both streaming online via zoom and in person in the Lyceum Room of the Husky Union Building on campus, and included UW faculty and staff, postdoctoral fellows, graduate students, and undergraduates. “The energy around all these [AI initiatives] that people are doing here makes me tremendously excited,” said Nathan Kutz, Senior Data Science Fellow and Adjunct Professor of Electrical Engineering & Physics. “We not only have a university that is incredibly collaborative, but we also have so much work going on in so many different domains.”
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The eScience Institute hosts a variety of hackweeks every year, which are designed to immerse participants in collaborative project work around a specific topic. Hackweeks try to blend elements of a hackathon, where participants work collaboratively in project teams, with tutorials on a variety of data science topics in an immersive and inclusive environment. eScience hackweeks provide a deep dive into an area of science with a focus on how data science methods and tools can be utilized to further research. For each hackweek, the program format evolves and is modified and adjusted to best suit the problem space and the user community. A great example of this process is the ICESat-2 Hackweek, which wrapped up earlier this year.
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The eScience Institute and UW Libraries Open Scholarship Commons recently co-hosted a workshop called “Python, your personal research assistant” for participants studying the humanities to explore the Python programming language and how to use it as a tool to aid in qualitative humanities work. Led by eScience Technical Education Specialist Naomi Alterman, the program encouraged students to decipher lines of Python, and learn how to make use of it to complete repetitive tasks. “I’m expecting folks to show up to the workshop with no experience with computer code,” Naomi Alterman said. “And I want them to leave with a suitable argument as to why it’s useful for them in the future.”
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Korena Mafune is a 2021 Washington Research Foundation postdoctoral fellow in the University of Washington’s Department of Civil and Environmental Engineering, where she studies the symbiotic interactions among plants, fungi, and bacteria. She received her PhD from UW’s School of Environmental and Forest Sciences, where she studied the root-associated fungal communities of old-growth bigleaf maple trees in Washington’s Queets and Hoh temperate rainforests. These trees accumulate layers of leaves and other organic matter on their canopy branches, which decay over time and produce a thick mat of organic soil high above the forest floor. Bigleaf maple trees have the capability to grow extensive adventitious rooting networks into these canopy soils which associate with fungal communities that thrive in the damp Pacific Northwest forests; some of these fungal associates attach to the roots and expand their fungal network outwards to aid the tree in taking up plant nutrients like nitrogen and phosphorus which the trees rooting system may not be able to reach on its own.
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Stuart Ian Graham is a graduate student in the University of Washington’s Biology program who recently published a paper with Senior Data Science Fellow and eScience Institute Research Scientist Ariel Rokem, along with others from the University of Washington, Université de Montpellier, and University of California Los Angeles. The paper, published in the Forests journal and titled “Regularized Regression: A New Tool for Investigating and Predicting Tree Growth,” initially grew from a 2019 Winter Incubator project at eScience, which paired Graham and Rokem together to utilize data science to explore how neighboring tree species can influence one another’s growth rates in Mt. Rainier National Park in Washington State.
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The University of Washington hosted the Data Science Minor Showcase several weeks ago, an event for undergraduates to explore the curriculum offered as part of the Data Science Minor program that was launched in Fall 2020. The showcase featured UW faculty outlining the new courses they have developed for the Minor, personal experiences from students who are currently enrolled in the minor, as well as smaller breakout sessions for participants to learn more about possible pathways towards data science from their areas of interest. One of the students who shared their experience with the Data Science Minor program was Stefan de Villiers, a UW senior who is majoring in Economics in addition to minoring in both Data Science and Mathematics.
The University of Washington’s Data Science Minor brings data science to a wide range of undergraduates within and beyond the STEM fields. 186 students are currently enrolled in the new minor, representing 54 areas of study at the university. UW undergrads interested in gaining literacy in data science methods and understanding their implications for society should look into adding a Data Science Minor to their studies. Ben Marwick, Senior Data Science Fellow and Director of the Data Science minor, described how the program will balance data skills and studies: “The goal is to combine the technical skills that relate to the new developments of generating and analyzing large amounts of data, then give students the context and the critical thinking skills to do something meaningful with that.”
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Over the past year, the University of Washington and UW Medicine have been at the heart of the city of Seattle’s Covid-19 response: researchers studying social distancing and how the virus spreads on our communities, volunteers collecting and distributing supplies, clinical vaccine trials, and a partnership with the city to process over 2 million test samples at no cost to residents – all of which have helped Seattle maintain one of the lowest Covid-19 rates of major US cities. And with so many departments and teams working together, often involving clinical patient data, an adaptable and secure info-sharing system is absolutely necessary.
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At the University of Washington, eScience Data Science Fellow and Research Assistant Professor of Psychology Ariel Rokem and UW Data Science Postdoctoral Fellow Adam Richie-Halford have created a way for the general public to help an algorithm learn to read MRI scans. Fibr utilizes the vast dataset of the Healthy Brain Network to better understand how mental health disorders are first diagnosed in childhood and adolescence. But in order for the algorithm to differentiate between scans that show long-range fiber connections in the brain and those that don’t, it must first learn what to look for. Regardless of scientific training, anyone who wants to participate can view a short tutorial and start guiding Fibr towards new innovations in neuroscience and beyond.
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