Dr. Michael Ajao-Olarinoye
Research Fellow & Lecturer in Computing | Applied ML, Generative AI & Physics-Informed Neural Networks
“Let’s build something amazing together.”
I’m a Research Fellow at the Centre for Computational Science & Mathematical Modelling (CSMM), Coventry University, advancing the HOPE-MOVE project with a completed PhD in Computational Science and Mathematical Modelling.
My research spans applied machine learning, generative AI, physics-informed neural networks, spatiotemporal epidemic forecasting, and cardiovascular hemodynamics.
Alongside research, I serve as a Lecturer in Computing at QAHE, teaching programming, data science, and machine learning through partnerships with Ulster University and Southampton Solent University — committed to making complex computational concepts accessible to diverse student cohorts.
Currently working on graph-attention models for epidemic forecasting, PINN surrogates for wall-shear-stress prediction, and generative AI workflows with strong data quality and ethical AI assurance.
Technology Stack
Python
R
Julia
Featured Research & Projects
A selection of research projects and implementations spanning physics-informed neural networks, cardiovascular hemodynamics, spatiotemporal epidemic forecasting, and applied machine learning.
Aneurysm Transient Flow Analysis with Physics-Informed Neural Networks
Advanced implementation of Physics-Informed Neural Networks for modeling transient blood flow dynamics in aortic aneurysms. This research combines deep learning with fundamental physics principles, incorporating Navier-Stokes equations to predict pressure distributions, velocity fields, and wall shear stress in both healthy and aneurysmal blood vessels.
Plant Disease Detection with Deep Learning
Cross-platform mobile application using artificial neural networks for plant disease detection. This MSc dissertation project achieved distinction and demonstrates the application of deep learning in agricultural technology for early disease identification and crop management.
Topic Modelling with Latent Dirichlet Allocation
Implementation of topic modeling techniques using Latent Dirichlet Allocation for text analysis and document classification. This project demonstrates natural language processing capabilities and unsupervised learning applications in text mining.
Publications & Presentations
Peer-reviewed publications, preprints, and conference outputs across physics-informed neural networks, cardiovascular hemodynamics, and spatiotemporal epidemic forecasting.
Publications
Modeling of Double Descending Thoracic Aortic Aneurysms Using Computational Fluid Dynamics (CFD) and Residual-Based Physics-Informed Neural Networks (ResNets-PINNs)
Authors: N. Fatima, M. Hamza, M. A. Farooq, Michael Ajao-Olarinoye
Venue: Pramana — Journal of Physics (Accepted for publication)
Accepted study combining computational fluid dynamics with residual-based physics-informed neural networks to model haemodynamics in double descending thoracic aortic aneurysms, advancing PINN surrogates for patient-specific vascular modelling.
A hybrid physics-informed neural network - SEIRD model for forecasting COVID-19 intensive care unit demand in England
Authors: Michael Ajao-Olarinoye, Vasile Palade, Fei He, Penny A. Wark, Zindoga Mukandavire, Seyedeh Mousavi
Venue: Recent advances in deep learning applications - Taylor Francis
This work presents a novel hybrid approach combining physics-informed neural networks with the SEIRD epidemiological model to forecast COVID-19 intensive care unit demand in England, bridging traditional mathematical modeling with modern AI approaches.
Fluid–structure interaction analysis of pulsatile flow in arterial aneurysms with physics-informed neural networks and computational fluid dynamics
Authors: M. Abaid Ur Rehman, Ozgur Ekici, M. Asif Farooq, Khayam Butt, Michael Ajao-Olarinoye, Zhen Wang, Haipeng Liu
Venue: Physics of Fluids - AIP Publishing
This study analyzes fluid–structure interaction in arterial aneurysms using physics-informed neural networks. We examined six vascular models (four diseased aortas with Marfan syndrome aneurysms and two healthy models) to evaluate wall shear stress and von Mises stress. Physics-informed neural networks demonstrated strong agreement with CFD results while significantly reducing computational cost.
Deep Learning Based Forecasting of COVID-19 Hospitalisation in England: A Comparative Analysis
Authors: Michael Ajao-Olarinoye, Vasile Palade, Seyedeh Mousavi, Fei He, Penny A. Wark
Venue: 2023 International Conference on Machine Learning and Applications (ICMLA)
A comprehensive comparative analysis of deep learning approaches for forecasting COVID-19 hospitalizations in England, evaluating various neural network architectures and their predictive performance for healthcare resource planning.
Preprints & Under Review
Comparative CFD Analysis of Wall Shear Stress in Healthy and Diseased Coronary Arteries and Saphenous Vein Grafts Using Physics-Informed Neural Network Surrogates
Authors: M. Ur Rehman, O. Ekici, S. Erdener, Michael Ajao-Olarinoye, A. G. Kuchumov, F. Jia
Venue: Submitted to Physics of Fluids
Morphology-Dependent Stress Localization in Thoracoabdominal Aneurysms: FSI Modeling with a Physics-Informed Neural Network Surrogate
Authors: M. Ur Rehman, H. Temimi, Michael Ajao-Olarinoye, A. Laadhari, M. Riahi, I. Kissami
Venue: Submitted to Physics of Fluids
MSAGAT-Net: Multi-Scale Temporal Adaptive Graph Attention for Efficient Spatiotemporal Epidemic Forecasting
Authors: Michael Ajao-Olarinoye, Vasile Palade, Fei He, Penny A. Wark, Seyedeh Mousavi, Zindoga Mukandavire
Venue: Submitted to Artificial Intelligence in Medicine (AIM) · Preprint on SSRN
Conference Presentations
Algorithmic Training Strategies for Physics-Informed Neural Network Wall Shear Stress Prediction in Cardiovascular Hemodynamics
3rd International Conference of Future Algorithms (online)
29–30 April 2026
Physics-Informed Neural Networks for Fluid-Structure Interaction Analysis of Arterial Aneurysms
2nd International Conference of Future Algorithms
July 2025
Physics-Informed Neural Networks for Modelling Infectious Disease Dynamics: A Case Study of COVID-19 in England
CSMM Conference, Coventry University
2024
Deep Learning Based Forecasting of COVID-19 Hospitalisation in England
International Conference on Machine Learning and Applications (ICMLA)
December 2023
Professional Experience
A comprehensive journey through academia, research, and industry, spanning teaching, software development, and business analysis.
Work Experience
Research Fellow
Coventry University — Centre for Computational Science & Mathematical Modelling (CSMM)
Coventry, United Kingdom
- •Advancing the HOPE-MOVE project through applied machine learning, generative AI, and interdisciplinary computational research.
- •Leading research activity spanning literature review, study design, data collection, model development, and evaluation of quantitative and qualitative outcomes.
- •Developing machine learning and generative AI workflows with strong data quality, ethical AI assurance, and responsible research practice.
- •Contributing to publications, collaborative proposals, and impact-focused activities while supporting student supervision and research-informed teaching.
Founder & CEO
miolajtech (RC KW10815)
Ikorodu, Lagos, Nigeria
- •Founded and lead miolajtech, a Nigerian tech and AI services company building tax, accounting, and productivity tools for SMEs and agricultural businesses across Nigeria and Africa.
- •Driving development of TaxPadi — a React Native, Expo, and Supabase mobile app that helps Nigerian SMEs manage finances, invoices, and tax obligations (VAT, CIT, PAYE, Capital Gains) under the Tax Reform Acts 2025.
- •Delivering client work including Papromakeovers — a Next.js booking website with availability management, EmailJS notifications, and Zoho invoicing integration.
- •Sharing engineering tutorials and product updates on the miolajtech YouTube channel.
Lecturer in Computing
QAHE Ltd
Birmingham, United Kingdom
- •Delivered high-quality teaching in computer science modules including Programming, Data Science and Machine Learning at Ulster University and Southampton Solent University through QAHE's university partnerships.
- •Designed and implemented course materials, assessments, and interactive learning activities aligned with university curricula and learning outcomes.
- •Provided academic support and mentorship to diverse student cohorts, employing inclusive teaching strategies to accommodate various learning styles.
Postgraduate Researcher
Coventry University
Coventry, United Kingdom
- •Produced peer-reviewed publications and conference outputs in applied machine learning, epidemic forecasting, and healthcare modelling, including presentations at the International Conference on Machine Learning and Applications (ICMLA).
- •Served as a Program Committee Member for the 23rd IEEE International Conference on Machine Learning and Applications (ICMLA), contributing paper reviews and conference planning.
- •Contributed to Coventry's research profile through interdisciplinary collaboration, postgraduate mentoring, and research dissemination across AI-driven and healthcare projects.
Graduate Teaching Assistant (Part-time)
Coventry University
Coventry, United Kingdom
- •Delivered tutorials, workshops, and one-to-one student support in the Electrical, Electronics and Computing department, adapting teaching approaches to diverse learners.
- •Supported student progression through assessment marking and constructive academic feedback.
- •Collaborated with module leaders on curriculum delivery and continuously sought peer feedback to improve teaching practice.
Software Developer
Tammy Tech
Lagos, Nigeria
- •Designed and developed web and mobile applications using technologies such as HTML, CSS, JavaScript, and Flutter, enhancing client product offerings by 30%.
- •Collaborated with clients to translate their needs into robust technical solutions, applying agile methodologies to deliver projects on time.
- •Integrated various APIs and built databases to support mobile app functionality, improving user experience and engagement.
Business Systems Analyst
Verificar Compliance
Lagos, Nigeria
- •Conducted business analysis and developed IT solutions to streamline company processes, resulting in a 15% improvement in operational efficiency.
- •Designed and implemented dashboards and reporting systems to track performance metrics, facilitating data-driven decision-making.
- •Analysed market trends and emerging technologies to inform product development strategies, positioning the company for future growth.
Awards & Recognition
Invited Speaker
3rd International Conference of Future Algorithms
Invited to present "Algorithmic Training Strategies for Physics-Informed Neural Network Wall Shear Stress Prediction in Cardiovascular Hemodynamics" at the 3rd edition of Future Algorithms (29–30 April 2026, online).
First Prize — Poster Competition
2nd International Conference of Future Algorithms
Won first prize for the poster titled "Physics-Informed Neural Networks for Fluid-Structure Interaction Analysis of Arterial Aneurysms."
Research Acknowledgement
Chinese Journal of Physics
Acknowledged for technical discussion that improved PINN results in Rehman et al. (2025), "Application of computational fluid dynamics and physics-informed neural networks in predicting rupture risk of thoracoabdominal aneurysms with fluid-structure interaction analysis."
Best Reviewer Award
CSMM Conference
Received recognition for outstanding contribution in reviewing conference papers and providing high-quality feedback to authors.
PhD Studentship Award
Coventry University
Awarded a fully-funded PhD studentship at the Centre for Computational Science and Mathematical Modelling (CSMM) to research resource allocation during pandemics.
Third Place in Community Development Project
KWASU Entrepreneurship and Innovation Challenge
Achieved third place for leading a community development project focused on youth empowerment through technology.
Ventures
Alongside research, I run miolajtech — a Nigerian tech and AI services company building products for SMEs, agriculture, and selected client engagements.
miolajtech
Founder & CEO
miolajtech builds tech and AI services for Nigerian and African SMEs and agricultural businesses — tax and accounting tools, client products, and custom AI-driven engineering.
Product suite
TaxPadi
Accounting and tax-management mobile app for Nigerian SMEs. VAT (7.5%), CIT (0/20/30%), PAYE, Capital Gains, and Development Levy calculators aligned with the Tax Reform Acts 2025 and Tax Administration Act 2026.
React Native · Expo · Supabase · Gemini (OCR)
Agriculture platform
Software for Nigerian and African agricultural operators — tackling data and tooling gaps across smallholder and enterprise agribusinesses.
Stack details to be announced
Papromakeovers
Next.js booking website with availability management, admin passcode protection, EmailJS notifications, and draft-invoice generation via Zoho.
Next.js App Router · Tailwind · Supabase · EmailJS · Zoho
Education & Development
Academic journey spanning engineering, data science, and computational research, complemented by active participation in professional development and community service.
Academic Qualifications
Doctor of Philosophy (PhD)
Computational Science and Mathematical Modelling
Awarded: February 2026
Thesis/Project: Data-Driven Algorithms for Forecasting Critical Care Demand during the COVID-19 Pandemic
Key Highlights:
- •Fully-funded PhD studentship at the Centre for Computational Science and Mathematical Modelling (CSMM)
- •Developed hybrid physics-informed neural network and epidemiological models for healthcare resource forecasting
- •Published in high-impact venues including Physics of Fluids and IEEE ICMLA
Master of Science (MSc)
Data Science and Computational Intelligence
Graduated with Distinction
Thesis/Project: Plant Disease Detection: A Cross-Platform Mobile Application Using Artificial Neural Networks
Key Highlights:
- •Key Modules: Machine Learning, Big Data Management, Advanced Machine Learning, Artificial Neural Networks
- •Achieved distinction in dissertation project
- •Developed cross-platform mobile application using deep learning
Bachelor of Engineering (BEng)
Electrical and Electronics Engineering
Second Class Honours
Thesis/Project: Designed and built a 2km Low-Power FM Transmitter
Key Highlights:
- •Key Modules: Engineering Mathematics, Digital Signal Processing, Control Engineering, Power Electronics
- •Vice President of Nigeria Union of Engineering Students Association (NUESA)
- •Strong foundation in electrical engineering principles and applied mathematics
Conference Participation
International Conference on Machine Learning and Applications (ICMLA)
Presenter & Program Committee Member
Conference Website →Computational Science and Mathematical Modelling Conference (CSMM)
Presenter & Best Reviewer Award Winner
Conference Website →Volunteer Experience
Software Engineering Team Manager
African Institute for Artificial Intelligence (AIAI)
Remote
Volunteer lead for AIAI's software engineering team, coordinating contributors and guiding engineering practice across the institute's software initiatives.
Lecturer
CodeYourFuture
Birmingham, United Kingdom (Remote)
Teaching programming and software development to underrepresented communities.
Project Manager for Gender Vanguard CDS
National Youth Service Corps (NYSC)
Nigeria
Managed community development projects focused on gender equality and youth empowerment.
Let's Collaborate
I'm always interested in discussing research opportunities, collaborations, and teaching partnerships across applied machine learning, generative AI, physics-informed neural networks, and data-driven modelling for healthcare and scientific computing.
Get in Touch
Whether you'd like to collaborate on a research problem, explore joint work in generative AI, physics-informed neural networks, or spatiotemporal epidemic forecasting, or discuss teaching and supervision, I'd love to hear from you.