Business Analytics & Computational Geometry
Integrating computational geometry and data science to drive business decision intelligence. Ideal for students targeting analytics leadership in industry and research—from spatial optimisation to reproducible ML pipelines.
Program Highlights
Decision Intelligence
Computational Geometry Studio
Industry Analytics Labs
Research-to-Product Path
Mentored Capstone
Open Tools Stack
Lead Faculty
Dr. Elena Boateng
Computational Mathematics
Dr. Elena Boateng specialises in numerical analysis, computational geometry, and high-accu…
View profileProf. Kwabena Mensah
Scientific Computing Laboratory
Prof. Kwabena Mensah leads research in computational fluid dynamics, industrial modelling,…
View profileDr. Sam Owusu
Applied Probability Group
Dr. Sam Owusu works on stochastic processes and uncertainty quantification for industrial …
View profileDr. Ama Serwaa
Geometry & Analytics Lab
Dr. Ama Serwaa develops geometric algorithms and spatial analytics for logistics, urban sy…
View profileDr. Joseph Addo
Decision Intelligence Unit
Dr. Joseph Addo focuses on machine learning for operations research, forecasting, and repr…
View profileProf. Linda Quartey
Graduate Studies Office
Prof. Linda Quartey leads interdisciplinary programmes linking applied mathematics with in…
View profileRequirements
Admission Requirements
- Bachelor's degree in mathematics, computer science, statistics, economics, or engineering.
- Comfort with linear algebra, probability, and at least one programming language.
- Motivation letter describing an analytics or geometry problem you want to explore.
- CV and two academic or professional references.
Career Outcomes
- Business intelligence and analytics engineering roles.
- Operations research and logistics optimisation teams.
- Further research in computational geometry or data science.
What You Will Build
Graduates leave with a portfolio of modelling notebooks, a geometric case study, and an industry-facing analytics deliverable.