Visualizing Complexity: Dimensionality Reduction and Network Science
Visualizing Complexity: Dimensionality Reduction and Network Science

Abstract: 

Working with mathematicians, data scientists, and domain experts at the University of Vermont Complex Systems Center, data visualization artist Jane Adams has developed strategies for prototyping exploratory graphs of high-dimensional data. In this 90-minute workshop, Adams shares some of these methods for data discovery and interaction, navigating a creative workflow from paper prototypes of visual hypotheses through web-based interactive slices, offering critical insight for clustering, interpolation, and feature engineering.

Bio: 

Jane Adams is the resident Data Visualization Artist at the University of Vermont Complex Systems Center in Burlington, VT, in partnership with the Data Science team at MassMutual Life Insurance. Adams collaborates with fellow researchers to make complex, temporally dynamic networks comprehensible through engaging, interactive visualizations. In her personal time, she builds interactive aquaponic ecosystems, generates digital data paintings of musical scores, and illustrates cartoon graphs inspired by the world around her. She is a community organizer with Vermont Women in Machine Learning & Data Science (VT WiMLDS) and an advocate for extradisciplinary inquiry. Stay in touch on Twitter @artistjaneadams

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