CfP: Applications of Topological Data Analysis to Big Data

***** Call for Papers: Workshop on Applications of Topological Data Analysis to Big Data at IEEE BigData 2021 *****

Topological Data Analysis (TDA) is a growing area of research that focuses on studying the “shape” of data. Tools (such as persistent homology) from TDA have been successful in many application areas, including signal processing, computer vision, dynamical systems, and geospatial systems. This workshop will be a venue for researchers and practitioners of TDA to present innovative, state-of-the-art topological methods and novel applications of topological tools to big data.In this workshop, we invite submissions on recent applications of topological data analysis, with a focus on larger datasets. Topics include but are not limited to:

  • TDA applications to graphs, hypergraphs and networks
  • TDA applications in natural language processing
  • TDA applications to image and video analysis
  • TDA applications in dynamical systems and signal processing
  • Topological approaches to spatial and social systems
  • Topological approaches to machine learning

Important Dates

  • September 30, 2021: Due date for full workshop paper submission (11:59pm AoE)
  • November 1, 2021: Notification of paper acceptance to authors
  • November 20, 2021: Camera-ready version of accepted papers due
  • December 15–18, 2021: Workshop (one day in this date range)

This workshop will be held remotely. Additional information can be found at https://www.egr.msu.edu/~tymochko/TDA_IEEEBigData2021.html.Thank you,
Tegan Emerson (Pacific Northwest National Lab)
Mason A. Porter (University of California, Los Angeles)
Sarah Tymochko (Michigan State University & Pacific Northwest National Lab)
Wlodek Zadrozny (University of North Carolina at Charlotte)

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