Michael Ajao-Olarinoye
PhD Researcher | Computational Science & Epidemiological Modeling
“Let’s build something amazing together.”
I’m a PhD Researcher in Computational Science and Mathematical Modelling at Coventry University, specializing in Physics-Informed Neural Networks (PINNs) and epidemiological modeling.
My research focuses on developing AI models that predict healthcare resource demand during pandemic scenarios, bridging the gap between traditional mathematical modeling and modern deep learning approaches.
With expertise spanning healthcare analytics, scientific computing, and educational technology, I’m passionate about making complex computational concepts accessible through both research and teaching.
Currently developing PINNs for aneurysm modeling, digital twin frameworks, and hybrid prediction models for pandemic preparedness and clinical decision-making.
Technology Stack
Python
Flutter
R
Julia
Featured Research & Projects
A selection of my research projects and implementations in biomedical engineering, physics-informed neural networks, and healthcare analytics applications.
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
Research contributions to the scientific community in biomedical engineering, physics-informed neural networks, and healthcare analytics applications.
Publications
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.
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.
Conference Presentations
Physics-Informed Neural Networks for Fluid-Structure Interaction Analysis of Arterial Aneurysms
2nd International Conference of Future Algorithms
July 2025
Deep Learning Based Forecasting of COVID-19 Hospitalisation in England
International Conference on Machine Learning and Applications (ICMLA)
December 2023
Epidemiological Modeling and Resource Allocation
Computational Science and Mathematical Modelling Conference (CSMM)
2024
Professional Experience
A comprehensive journey through academia, research, and industry, spanning teaching, software development, and business analysis.
Work Experience
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
- •Authored peer-reviewed publications and presented research at prestigious conferences, including ICMLA, significantly contributing to institutional research output.
- •Developed and delivered tutorial sessions, workshops, and individual student support for Electrical, Electronics and Computing department.
- •Served as a Program Committee Member for the 23rd IEEE International Conference on Machine Learning and Applications (ICMLA).
- •Mentored postgraduate students and collaborated with interdisciplinary teams on AI-driven and healthcare projects.
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
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.
Best Reviewer Award
CSMM Conference
Received recognition for outstanding contribution in reviewing conference papers and providing high-quality feedback to authors.
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."
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.
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
Expected Graduation: July 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)
- •Research focus on epidemiological modeling using Physics-Informed Neural Networks
- •Published in high-impact journals including Physics of Fluids and IEEE conferences
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
Group Head of AI Literacy
African Institute for Artificial Intelligence (AIAI)
Remote
Leading AI literacy initiatives across African communities, developing educational programs and resources.
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.
Skills & Expertise
A comprehensive skill set spanning research, development, and leadership, built through academic pursuits and professional experience.
Technical Skills
Research & Modeling
- •Physics-Informed Neural Networks (PINNs)
- •Epidemiological Modeling
- •Deep Learning (RNNs, LSTMs, CNNs, Transformers)
- •Scientific Computing
- •Numerical Methods
Programming & Frameworks
- •Python (TensorFlow, PyTorch, JAX, SciPy)
- •Machine Learning (Scikit-learn, Keras)
- •Data Science (Pandas, NumPy, Statistical Analysis)
- •Visualization (Matplotlib, Seaborn, Plotly)
- •Julia Programming
Engineering & Development
- •Electrical Engineering (Communications, Signal Processing)
- •Web Technologies (JavaScript, HTML5, CSS/SCSS, ReactJS)
- •Mobile Development (Flutter)
- •Cloud Computing (AWS, Azure, Google Cloud)
- •Version Control (Git, GitHub)
Data & Analytics
- •Big Data Management
- •Data Visualization
- •Statistical Methods
- •Information Retrieval
- •Database Design
Professional Skills
Communication
Strong ability to explain complex technical concepts to non-experts
Problem-Solving
Strategic and analytical problem-solving approach
Leadership
Experience mentoring junior developers and data scientists
Teaching
Skilled in making complex concepts accessible at various levels
Collaboration
Extensive experience working in cross-functional teams
Time Management
Expertise in managing multiple projects and meeting deadlines
Let's Collaborate
I'm always interested in discussing research opportunities, collaborations, and innovative projects in epidemiological modeling, physics-informed neural networks, and interdisciplinary AI applications.
Get in Touch
Whether you're interested in research collaboration, discussing innovative approaches to epidemiological modeling, or exploring opportunities in physics-informed neural networks and interdisciplinary AI applications, I'd love to hear from you.