Special Interest Groups

  1. Using Data Science /
  2. Special Interest Groups

The eScience Institute is excited to launch an open and ongoing call for Special Interest Groups (SIGs).

eScience SIGs are flexible and dynamic structures that support the development of new connections and communities on diverse data science related topics. Learn more about proposing a new SIG.

Satellite Image Analysis

Group Chairs: Valentina Staneva & Amanda Tan

This special interest group utilizes satellite imagery data sets provided by both federal institutions and private companies to answer questions in a variety of domains.

Computational Demography Working Group (CDWG)

Group Chairs: Connor Gilroy, Neal MarquezLee Fiorio, Tim Thomas, Sara CurranMatt Dunbar & Jon Wakefield

The CDWG discuss topics related to: demographic data and computational and statistical methods, share students & faculty tools, develop via demos or tutorials, and graduate student & faculty research workshops. This group is hosted jointly with the UW Center for Studies in Demography and Ecology.

Institute for Foundations of Data Science Institute (IFDS)

Group Chair: Maryam Fazel

The NSF-funded Institute for Foundations of Data Science (IFDS) is led by UW and is a collaborative partnership with teams at the universities of Wisconsin-Madison, California-Santa Cruz, and Chicago. IFDS brings together researchers from computer science, electrical engineering, mathematics, and statistics to make progress along its four themes of research (complexity, robustness, closed-loop data science, and ethics & algorithms), towards more robust, reliable, privacy-preserving, fair data science algorithms that perform well in dynamic environments.

Environmental Impacts of Data Science

Group Chairs: Dave Beck & Emily Keller-O’Donnell

The computational activities of data science draw on cyberinfrastructure systems that are built, powered, and maintained using renewable and carbon-based energy sources and other natural resources. The externalized impacts that result are influenced by many factors, from data center design to AI modeling trends and cloud data storage policies. This interdisciplinary group explores ways to incorporate sustainability principles into data, computer and information sciences, for practitioners and educators. Click here to get involved.

Legacy Groups

Legacy groups are Special Interest Groups that are no longer current, although the archived information may still be useful, or lead to new collaborations in the future.

Reproducible and Open Research

Group Chair: Ben Marwick

This group aims to promote the alignment of scientific ideals with research behaviors in the UW community. We fulfill this aim by sharing information, facilitating training and development – especially about open source scientific software – and working to implement sustainable campus policies to support transparency, open sharing, and reproducibility.

Data Science Education and Career Paths

Group Chairs: Tyler McCormick and Sarah Stone

This group develops innovative teaching methods and formats to make both formal and informal training in data science skills more accessible within and beyond the UW. We also focus on how to create and sustain long-term career trajectories for a new generation of researchers whose work depends crucially on the analysis of massive, noisy, and/or complex data.


Group Chairs: Spencer Wood & John Wilkerson

Text is a ubiquitous and valued data source in the computer and information sciences, many areas of the natural and social sciences, engineering, business and more. This eScience Special Interest Group is for students, faculty and researchers interested in sharing and learning about UW research and teaching that uses text as data.

Data Science Studies

Group Chairs: Anissa Tanweer & Cecilia Aragon

UW Data Science Studies was a group of cross-disciplinary researchers interested in the sociocultural and organizational dimensions of data science. It existed to create opportunities for discussing research, reading scholarly work related to this subfield, supporting research collaborations, and leveraging sociotechnical perspectives to inform data science practice. The group convened from 2015 – 2021, and materials from their activities, including slides and video recordings, can be accessed through the archived website below.


Group Chair: Ariel Rokem

The neuroinformatics special interest group at the University of Washington (UW) eScience Institute and the University of Washington Institute for Neuroengineering (UWIN) focuses on neuroinformatics methods and their role in understanding the brain.

Graphs and Networks – Theory and Applications

Group Chairs: Alice Schwarze & Spencer Wood

Thinking about data and complex systems as networks and using tools of network analysis has been a successful approach in various research problems. Many fields that have benefited from network approaches — e.g., systems biology, neuroscience, biomedicine, engineering sciences, and social sciences — have very active research communities at UW. Our SIG aims to create opportunities and spaces for researchers at UW and their colleagues to meet, learn, and discuss the connections between their research and network science.

Quantitative Cell Biology and Communities (QCBC)

Group Chairs: David Beck & Joseph Hellerstein

Rapid progress in the quality and quantity of laboratory data on cellular processes enable the development of quantitative models of cells and cell communities that can usher in a new era of materials, personal medicine, environmental remediation and more. We refer to this emerging area as Quantitative Cell Biology and Communities (QCBC). The QCBC special interest group at the eScience Institute focuses on data management, processing pipelines, and modeling, and machine learning methodologies for understanding the biology of cells, viruses, and their communities.

Remote Hackweeks

Group Chairs: Anthony ArendtDaniela Huppenkothen & Charley Haley

The Remote Hackweeks Working Group shares lessons learned as we transition community building and educational activities to a remote environment. Together we are developing resources to support our collective efforts to build inclusive and welcoming communities using remote technologies.

Working Spaces and Culture

Working Group Leads: Micaela Parker & Sarah Stone

Establish new physical spaces on our campuses, specifically designed to meet the new requirements of data science activities, which in many cases will flourish best outside of traditional departmental boundaries.