La Matematica

The goal of this volume is to provide examples of contemporary results and research related to quantitative justice and the intersections of data science and social justice. The theme of the volume is work that uses quantitative and qualitative techniques to address contemporary social justice issues.

Quantitative Justice (QJ) is defined as “the application of techniques, tools and topics from various quantitative sciences (e.g., applied mathematics, data science, computer science, etc.) in subject domains that are derived from the social sciences (e.g., political science, law, economics, etc.) with the goal of promoting social justice.” Data Science for Social Justice (DS4SJ) is broadly defined as “data scientific work (broadly construed) that actively challenges systems of inequity and concretely supports the liberation of oppressed and marginalized communities.” We believe that QJ is the more expansive term so we have selected this as the title of the volume, although we will happily accept work firmly characterized as DS4SJ.

Submission Deadline: November 1, 2024

Guest Editors:

• Omayra Ortega (Sonoma State University, USA)
• Carrie Diaz-Eaton (Bates College, USA)
• Ron Buckmire (Occidental College, USA)
• Joseph Hibdon, Jr. (Northeastern Illinois University, USA)
• Tian-An Wong (University of Michigan-Dearborn, USA)
• Victor Piercey (Ferris State University, USA)

This topical collections aims to present a multitude of uses of Monte Carlo methods driven by diverse applications in cutting edge fields of research including biological and neural network modeling, disease spreading, RNA dynamics, granular materials, and water filtration. We invite manuscripts focused on algorithm development as well as updates of existing methods in the context of a specific real-world application.

Submission Deadline: 31 August 2025, then rolling
Guest Editors: Francesca Bernardi, Worcester Polytechnic Institute (USA); Andrea Arnold, Worcester Polytechnic Institute (USA)

Research in tensor (multidimensional array) analysis is accelerating, driven by the increasing complexity of data sets, arising from fields such as biomedical engineering, networks, and the physical and social sciences, which naturally lend themselves to a tensor structure. Tensor factorization methods in particular have been shown to aid in low-dimensional embedding and clustering, data compression, denoising, and imputation.  We invite submission of research, survey, and review articles on novel theoretical, computational, and real-world application progress in tensor analysis.

Submission deadline: 1 June 2024
Guest Editors: Dr. Jamie Haddock, Harvey Mudd College (USA); Dr. Anna Konstorum, Center for Computing Sciences, Institute for Defense Analyses (USA) and University of Florida (USA); Dr. Anna Ma, UC Irvine (USA)

This topical collection aims to bring together works focused on mathematical modeling of the eye with the shared goal of improving ocular health and ophthalmic treatments. Ocular health determines our quality of life as our eyes provide much of the information we receive about the world. We welcome contributions in which mathematical models, empirical to mechanistic, are used to develop new and significant understanding of ocular health and treatments. Submitted works should have a high level of originality and quality.

Submission Deadline: 1 February 2024

Guest Editors: Lucia Carichino, Rochester Institute of Technology (USA); Kara Maki, Rochester Institute of Technology (USA)