About this journal
Applied Network Science (ANS) is an open-access and strictly peer-reviewed journal giving researchers and practitioners in the field the ability to reach a larger audience. ANS encompasses all established and emerging fields that have been or can be shown to benefit from quantitative network-based modeling. Contributions from all fields of science, technology, medicine and humanities will be considered, in particular from newly emerging research areas formed and developing at the interfaces of presently established sub-disciplines.
The focus of the journal is based on novel or anticipated applications of network sciences, on related techniques that may be used in applications of complex network methodologies, and on innovative modeling approaches that will enhance specific applications and lead to more widespread use of network science concepts. Contributions from all fields of science, technology, medicine and humanities will be considered, with an emphasis on articles that have direct applications to real world problems.
Hocine Cherifi is a Professor of computer science at the University of Burgundy in Dijon, France. He obtained his Ph.D. degree at the National Polytechnic Institute in Grenoble, France. He has held faculty positions at Rouen University and Jean Monnet University, as well as visiting positions at Yonsei, Korea, University of Western Australia, National Pintung University, Taiwan and Galatasaray University, Turkey. His work is focused on computer vision and complex networks.
Ronaldo Menezes is a Professor of computer science at the Florida Institute of Technology, where he also acts as Director of the BioComplex Laboratory. After studying computer science at the University of Fortaleza and State University of Campinas, in Brazil, he completed his Ph.D. studies on parallel and distributed systems at the University of York, UK. The main focus of his research is on coordination systems, swarm Intelligence and complex Networks.
- Applied Network Science
- Springer International Publishing
- Volume 1/2016 - Volume 6/2021
- Electronic ISSN
- Journal ID