I am a Lecturer in Algorithms and Complexity in the School of Computing Science at the University of Glasgow. I have a PhD in Computing Science from the University of Glasgow, Scotland; an MSc in Mathematical Sciences from the African Institute for Mathematical Sciences (AIMS), Ghana; and a BSc in Mathematics from the University of Ibadan, Nigeria. My journey from being a major in Mathematics to becoming a researcher in CS is fuelled by my passion for problem solving and programming.
I am also very passionate about using my skills to help people. In my spare time, I find myself reflecting on how best to inspire and pass on computing skills to young Africans studying in a STEM related field, with the hope that they can also grow to become creative thinkers. Consequently, they can contribute to pushing Africa forward on the frontiers of science and technology. All of these thoughts and reflections led to PWSAfrica - an initiative focused on empowering scientists in Africa with computer programming skills. In recognition of the significance of this initiative, I was named as one of the Future World Changers at the University of Glasgow.
For sports, I enjoy weightlifting, boxing, high-intensity training and pilates. I am an active member of the University of Glasgow gym. However, since the global pandemic started, I have resulted to walking! I walked half a million steps in June 2020 (roughly 13km daily in 18,000 steps). Since I started my new job in August 2020, I have settled for an average of 10,000 daily steps.
I am a member of the Formal Analysis, Theory and Algorithms (FATA) research group. My motivation for research is fuelled by my passion for using tools from mathematics and computer science to solve real-world problems. I recently completed my PhD (awarded July 2020), and my work was on the design of efficient algorithms for matching problems.
Matching problems arise when we seek to match a set of agents to a set of objects (e.g., pairing donor kidneys with transplant patients, allocating junior doctors to hospitals, and assigning students to projects). Typically, agents may have ordinal preferences over a subset of objects, and there may be constraints on the number of agents that each object can accommodate. A natural goal is to find an optimal allocation of agents to objects, according to the given preferences and constraints. A practical application of matching problems, where university departments seek to allocate students to dissertation projects, is referred to as the Student-Project Allocation problem (SPA). My thesis presents new structural results, as well as efficient (polynomial-time) algorithms for variants of SPA.
I am founder and lead of Programming Workshop for Scientists in Africa (PWSA ) - an initiative focused on empowering scientists in Africa with computer programming skills. PWSA is an international outreach supported by the School of Computing Science, University of Glasgow.
hopcroftkarp 1.2.4: A Python library that finds a maximum matching in bipartite graphs.