Network and Graph Theory

Dr. Kenneth Dadedzi

The area of my research is in Spectral Graph Theory, which involves studying eigenvalues of matrices associated with graphs. I completed my master’s and Ph.D Degrees at Stellenbosch University and was part of the African Institute for Mathematical Sciences (AIMS) South Africa 2013/2014 intake. I completed my undergraduate degree at Cape Coast University in Ghana. I’m currently a Lecturer at the Department of Mathematics at the University of Ghana. My current research on the eccentric sequence and set of a graph. Specifically, their relation to graph spectrum. I am also working on the application of graph theory to bio-mathematics.


Dr. Fadekemi Osaye

Dr Fadekemi Janet Osaye is a mathematician whose primary research interests are discrete mathematics and combinatorics. In particular, she is interested in distance measures in graphs and their applications to solving many real-world problems like networks. Her interest in discrete mathematics was inspired by her research project carried out at AIMS Ghana. In 2019, she became the first black female to be awarded a PhD in Mathematics by the University of Johannesburg, South Africa, in its 116 years of its existence. Since June 2021, she has been an Assistant Professor of Mathematics at Alabama State University and was previously a Visiting Assistant Professor at Auburn University. She is the founder of Girlsmatics Foundation, a STEM non-governmental organization for girls in Nigeria. She was motivated by her involvement with AIMS Ghana’s outreach programs for high school students in Biriwa, Ghana. She is also the co-founder of FadNna Partners, an analytics and management firm based in Abuja and Lagos, Nigeria.

Abstract:

Modeling and analysis with complex networks have emerged as a prominent interdisciplinary field that facilitates the study of intricate systems in diverse domains. Complex networks, characterized by their non-trivial topological structures and interconnected components, provide a versatile framework to comprehend and interpret complex phenomena in fields such as biology, social sciences, computer science, and physics.  This abstract highlights the significance of complex network modeling and analysis in unraveling the underlying mechanisms governing real-world systems. Through the representation of nodes and edges, complex networks capture the interactions, dependencies, and emergent behaviors of interconnected elements, offering a powerful tool to study system dynamics and identify critical components. 

Software Required: Python Package NetworkX, Gephi Software (Can be downloaded for free), SageMath, Mfinder, and igraphs.

Lecture Materials