A.V. Dossou-Olory, A., & A. Mojeed, S. (2025). Matula Numbers and their Applications. IntechOpen. doi: 10.5772/intechopen.1006120. Click this link to download: https://www.intechopen.com/online-first/1193404

During my research assistantship at the Santa Fe Institute, under the guidance of Dr William Tracy and Dr Emma Zajdela, I developed an algorithm to facilitate the assembling of culturally diverse and interdisciplinary groups at conferences. The algorithm minimizes the frequency of repeated meetings among pairs and the tendency to assign individuals who have had substantial discussions about research or have formally collaborated on a paper to the same group, thereby combating homophily and preferential attachment at conferences. Click here to explore a web application powered by the algorithm.

In the winter of 2024, I led a group of three mentored by Dr Emma Zajdela on an interdisciplinary research project to examine whether homophily effects influence the choices made by Scialog conference attendees when choosing their collaborators. I modeled the collaboration networks that were formed by the fellows who attended three conferences and determined their mixing patterns using assortativity coefficients. The project aims to determine whether the use of group formation algorithms at Scialog conferences prevents homophilic collaboration among participants. Notably, my group’s project was ranked in the top 3 out of the 15 projects that emerged from the Santa Fe Institute (SFI) 2023 Complexity Global School, and we were invited to SFI as a prize to continue research. For more information, please see the Princeton Department of Ecology and Evolutionary Biology article:  https://eeb.princeton.edu/news/emma-zajdelas-group-mentees-receive-santa-fe-institute-prize.

I was one of the 14 competitively recruited students who participated in the Africa-Oxford Mathematics Virtual Mentorship Programme in 2023. The fully funded virtual program, organized by the Mathematical Institute of the University of Oxford, aimed to support a small cohort of promising pre-PhD students in mathematical sciences from Sub-Saharan Africa. The program offered networking opportunities and career training on topics such as research integrity, scientific writing, and public engagement with research. As part of the programme, I was supervised by Dr. John Pougue-Biyong and completed a mini-project titled "Centrality-based Optimization of Mobility in a Transportation Network." 

The project aims to examine the extent to which local perturbations have global, far-reaching effects on the mobility of an urban transportation system. To achieve this, we analyzed the multimodal transportation network, including buses, metros, coaches, and rail, in London, Manchester, and Oxford (United Kingdom). We show that the closure of a few central locations (local perturbation) increases mobility difficulty throughout the entire transportation network (global effect). With this observation in mind, we conduct optimization-based, data-driven simulations to provide decision-makers with practical recommendations for mitigating the impact of such closures. For more information about the program, please see the University of Oxford Mathematical Institute’s website.

My master's essay (thesis) examines a bijective map between the sets of rooted trees and natural numbers. In this paper, I reviewed a bijective function between the set of rooted trees and the set of natural numbers. The function assigns each rooted tree T (up to isomorphism) a natural number known as the Matula number of T. I discussed several results that enable the determination of statistics—such as the number of vertices, leaves, diameter, height, and so on—of rooted trees directly from their Matula numbers. Finally, I provided a review of the proof for the trees assigned the maximum and minimum Matula numbers among all rooted trees with a given number of vertices. Please see my publication above for more information.

In my first mini-project, I analyzed a food web network representing the South Florida Everglades to identify the primary producer responsible for the survival of most organisms in the network — that is, the most central node. To achieve this, I determined the network's statistics, visualized its degree distribution, and calculated the centrality of its nodes.

In my second mini-project at AIMS, I studied the applications of Dijkstra's algorithm and used it to determine the shortest paths between all pairs of nodes in a synthetic network. This algorithm has applications in the study of transportation networks, supply chains, and courier services.