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Copy file name to clipboardExpand all lines: about.md
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Individual Bios
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Roles or Contributions (optional, only if it makes sense to your team)
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**Jihyeon Bae, Student Fellow**
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Ph.D. Candidate
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Political Science, University of Washington
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Jihyeon Bae is a PhD candidate in the Political Science Department at the University of Washington. She is interested in comparing design choices around international organizations and how they influence cooperation among states. She is also passionate about applying NLP models to explore how rhetoric changes in international forums like the United Nations General Assembly. During the UW DSSG program, she will work on a project assessing water reuse patterns, based on substantive knowledge in actor-based institutional design. Born and raised in South Korea, she received her B.A. in International Studies from Kyung Hee University in 2019, with additional training from the Applied Mathematics Department.
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**Nora Povejsil, Student Fellow**
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Master’s Student
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Information and Data Science, University of California, Berkeley
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Nora Povejsil is a Master’s student studying Information and Data Science at the University of California, Berkeley. Nora’s dedication to using her technical skills for good was recognized through the Jack Larson “Data for Good” Fellowship award she received during the 2023-2024 academic year from her university.
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Her educational background includes a double major Bachelor’s degree in Data Science and Public Health from UC Berkeley. During that time, she served as an Undergraduate Student Instructor for a class on the U.S. healthcare system. Driven by a desire to address public health inequities, Nora sought out experiences to advocate for underserved communities in women’s healthcare as a Medical Assistant for the Midwifery unit at the Hennepin County Medical Center in Minneapolis and as a volunteer at the Daytime Women’s Drop-In Center in Berkeley.
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Nora also has a strong passion for environmental work. She applied her data science skills as an Undergraduate Research Assistant for the Power Lab, an integrative biology/ecology lab, creating machine learning algorithms to identify fish species and track ecological patterns and migration trends in Northern California.
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**Mbye Sallah, Student Fellow**
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Master’s Student
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Applied Economics, Ohio University
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Mbye is currently pursuing a master’s degree in applied economics at Ohio University. He also holds dual bachelor’s degrees in Economics and Finance and Banking from Suleyman Demirel University. Being from a low-income country, The Gambia, his research interest focuses on development economics, specifically financial development, and household welfare. Realizing the potential of data science in unraveling complex societal problems and motivated by his commitment to bridging the gap between economic theory and practical solutions, he is eager to join the DSSG fellowship. With a background in economics, he hopes to enhance his data science skills, which he can utilize to understand and provide practical solutions to societal issues.
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**Daniel Vogler, Student Fellow**
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Master’s Student
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Data Science, University of Washington
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I am currently pursuing a Master’s degree in Data Science at the University of Washington. Before graduate school I worked as a management consultant, primarily supporting clients in healthcare and retail. I graduated with a B.A. from Princeton University in 2021. I am deeply interested in the intersection between data science, machine learning, and energy, especially in data-driven approaches to energy policy. I am excited to participate in the DSSG program for the opportunity to further explore how data science can help communities pursue sustainable development as part of the Water Reuse project.
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Where readers can find more details about the project, e.g. code, data, reports, etc.
Communities around the United States are thinking of alternative water systems to address local water challenges. One example of this is water reuse, which is defined by the Environmental Protection Agency (EPA) as “the practice of reclaiming water from a variety of sources, treating it, and reusing it for beneficial purposes.” The current social problem is that communities only see water reuse as an opportunity for areas that are experiencing water scarcity, rather than realizing it’s full potential to address a wide range of water challenges, like reducing combined sewer overflows, minimizing the nutrients that are discharged to the environment, and lowering flood risk.
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Our project aims to address this social problem by developing a framework for quantifying a community’s potential for water reuse based on various motivators—or drivers—to identify whether water reuse could be a local solution that merits further investigation. Combining that data into an informative index and presenting the results in a clear and digestible format is critical for supporting local decision-making. Using publicly available data across the US, our project looks at the correlation between drivers (both presence and intensity) and characterizes the benefits communities might find by exploring water reuse. Outcomes from this work will be synthesizing these relationships into an interactive storymap for effective, real-world use of the research by local communities, engineers, and decision-makers.
Copy file name to clipboardExpand all lines: motivation.md
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**Questions**
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There are two main goals for this project:
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-Creating a general tool that allows users to create their own index of interest and map it on the US continental map.
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-Create a general tool that allows users to create their own index of interest and map it on the aims at enabling users with R coding skills to create an index of interest on the US map at varying geo-spatial scales, and then build their own website to visualize that index.
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- Use this tool to create a set of deliverables for stakeholders in the water sector to assess and prioritize areas based on their potential benefit from investing in water reuse infrastructure.
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