Call for Papers on Data Science on Graphs

Guest Editor: Santiago Segarra (Rice University, USA), e-mail:
APCT Editor: Gunnar Carlsson (Stanford University, USA)

There is a fast-growing interest in developing models and tools for analyzing data and capturing the intricate interactions in complex systems such as biological, technological, and social networks. However, the data associated with these systems is typically high-dimensional and irregular, posing novel challenges to classical data science methodologies. To cope with these challenges, the fields of graph signal processing and geometric deep learning have respectively extended classical signal processing tools and machine learning principles to data defined on graphs. An alternative set of tools to handle complex data has been developed within the field of topological data analysis, which concerns itself with the modeling of data sets by geometric objects such as graphs or simplicial complexes.

The Journal of Applied and Computational Topology (APCT) would like to encourage the interaction of those working in topological data analysis with those working in the rich area of machine learning and signal processing on graphs by publishing a special issue devoted to the largely unexplored intersection between these fields.

Topics of interest include but are not limited to:

  • Topological data analysis on (multi-layer) graphs and higher-order networks
  • Fourier and wavelet analysis on graphs
  • Graph topology inference from network data
  • Robust and non-linear processing of network data
  • Machine learning on graphs: kernel-based techniques, clustering methods, scalable algorithms
  • Graph neural networks: Theory, properties, architectures, and geometry
  • Graph representation learning
  • Applications to neuroscience, bioengineering and bioinformatics
  • Applications to communications, power, and transportation networks
  • Applications to finance, economic, and social networks
  • Applications to image, speech, and video processing

Important information

Submission Deadline:  June 22, 2022

Manuscripts should be prepared according to the submission guidelines of the journal.

All papers must be submitted to the journal's submission system. During the submission stage, please select "Yes" for the question "Does this manuscript belong to a special feature?" in Additional Information tab, then select a special feature "S.I.: Data Science on Graphs".