Research in Computational Topology 2

This volume showcases the research of women in applied and computational topology, including topological data analysis, neural networks, and approximation by digital grids. The workshop featured senior researchers and two of the field's pioneers.

Format: Hardback
Length: 294 pages
Publication date: 11 May 2022
Publisher: Springer Nature Switzerland AG

This second volume of Research in Computational Topology is a vibrant celebration and enthusiastic promotion of research by women in applied and computational topology. It encompasses the proceedings of the second workshop for Women in Computational Topology (WinCompTop), as well as papers solicited from the broader WinCompTop community. The multidisciplinary and international WinCompTop workshop offered an exhilarating and one-of-a-kind opportunity for women from diverse locations and research specializations to engage in extensive and collaborative discussions, ultimately contributing to the development of new and dynamic research directions within the field. The esteemed senior researchers who assumed leadership roles in the workshop are global pioneers in their respective disciplines, and two of them have authored some of the pioneering papers in the field.

Among the featured topics in this volume are:

- Topological Data Analysis of Power Law Structure in Neural Data: This research explores the analysis of neural data using topological methods, specifically focusing on the identification of power law structures and their implications in understanding brain networks.

- Nerve Theorem for Directional Graph Covers: This theorem establishes a connection between the topology of directional graphs and the concept of graph covers, providing insights into the structural properties of directed networks.

- Topological or Homotopical Invariants for Directed Graphs Encoding Connections Among a Network of Neurons: This study investigates the use of topological or homotopical invariants to characterize directed graphs, which represent connections among neurons in the brain. It explores the potential of these invariants for understanding brain function and behavior.

- Approximation of Objects by Digital Grids: This research examines the approximation of objects by digital grids, including the development of precise relations between the persistent homology of dual cubical complexes and the digital representation of objects.

The contributions made by the participants and speakers at the WinCompTop workshop are truly remarkable, showcasing the immense talent and dedication of women in the field of computational topology. This volume serves as a testament to their achievements and serves as a catalyst for further progress and collaboration in this exciting and rapidly evolving area of research.

We would like to extend our heartfelt gratitude to all the contributors, organizers, and sponsors who made this volume possible. Your support and dedication have played a vital role in promoting diversity and inclusivity in computational topology.

We hope that this second volume of Research in Computational Topology will inspire and empower women to continue their groundbreaking work in this field, and we look forward to witnessing the continued growth and success of women in computational topology in the years to come.

Weight: 629g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030955182
Edition number: 1st ed. 2022