About me
Dr. Habeeb Balogun has nearly a decade of academic and industry experience in data science and artificial intelligence. Before joining the University of Westminster, he worked as a senior machine learning engineer at BDTI, where he specialised in the development and deployment of AI-powered solutions to solve complex real-world problems.
He has made substantial contributions to a range of UK Research and Innovation (UKRI)-funded projects, highlighting his strong engagement in interdisciplinary research. Habeeb played key roles in the successful delivery of several completed UKRI projects, all of which addressed critical challenges across sectors such as healthcare, sustainability, infrastructure, and smart technologies. Habeeb continues to contribute to ongoing research, supporting innovation in data science and AI across multiple domains, and would be interested in research collaborations.
Teaching
Habeeb is a Fellow of the Higher Education Academy (FHEA). He serves as the module leader for Data Engineering (5DATA005W) and Machine Learning in Practice (7DATA001W).
Habeeb is also a tutor in several modules such as Software Development I (4COSC001W), Software Development II (4COSC005W), Data Mining and Machine Learning (7BUIS008W), Data Warehousing and Business Intelligence (7BUIS010W), Web and Social Media Analytics (7BUIS025W), and Data Visualization and Dashboarding (7BUIS009W), final year project supervision (6COSC023W), and MSc project supervision (7COSC012W).
Research
Habeeb's research is focused on applying contemporary technologies (artificial intelligence, machine learning, deep learning, natural language processing/LLM, and IoT) to solve real-world problems across different domains. A few from the UKRI projects Habeeb has contributed to include:
Locally made solar home system for affordable mini off-grid - Powerbox; Funder: Innovate UK; total Value: £233,559; Start–End Dates: 2024–2025
LINK – Creating a digital direct connection between owners and buyers of salvage construction material (Circular Economy); Funder Innovate UK; Total Value: £392,765; Start–End Dates: 2023–2024
Artificial Intelligence Reviewer of construction contract for subcontractor (Aircons); Funder: Innovate UK ; Total Value: £49,496 ; Start–End Dates: 2023–2024
Pollution Avoidance Support System (PASS) using GIS, Machine Learning, and big data; Funder: Innovate UK; Total Value: £393,712 ; Start–End Dates: 2021–2023
Publications
For details of all my research outputs, visit my WestminsterResearch profile.