Projects led and built by us

My research focuses on AI-assisted approaches for resource coordination, logistics planning, operational risk assessment, predictive maintenance and multi-stage decision-making across interconnected warship systems.

The project also examines verification and validation requirements for safety-critical AI systems, including explainability, auditability, comprehensive testing, exception handling and human-in-the-loop approval. The proposed framework ensures that critical operational decisions remain under the control of authorised personnel.

My responsibilities include independent research, AI solution design, mathematical and statistical modelling, operational workflow analysis, risk-based decision-system design, verification and validation planning, technical documentation and project management.

I contribute to the design and development of AI models for mosquito detection, species classification, automated egg counting and uncertainty-aware multimodal decision-making. The proposed system combines camera images, wingbeat signals, environmental data and geospatial information to support accurate mosquito surveillance.

The project also explores low-power edge AI, solar-powered monitoring devices, cloud-based workflows and human-approved public health alerts. Its objective is to support early dengue-risk detection, improve mosquito surveillance and assist public health teams with timely, evidence-based interventions.

The system allows authorised users to add, edit, delete and manage medical supply records, including item codes, descriptions, purchase prices, available stock and reorder levels. When stock reaches or falls below the defined reorder level, the system automatically generates a reorder notification for the administrative team.

I contributed to the system design, backend development, workflow automation, database management, authentication, AI integration foundations and cloud-ready implementation. The project also includes an LLM-agnostic AI gateway designed to support future LangGraph, LangChain and intelligent procurement workflows.

I am contributing to the design and development of AI-powered driver matching, delivery partner allocation, route optimisation, demand forecasting, dynamic service coordination and automated workflow management. The platform is designed to connect customers, drivers, delivery partners, restaurants, merchants, franchise operators and administrators through integrated mobile applications and management portals.

My responsibilities include AI feature development, project planning, MVP definition, business workflow design, technical coordination, marketplace development, database planning, cloud deployment strategy and product roadmap management.

The project is being developed in phases, beginning with the taxi service, followed by food delivery integration and expansion into a scalable multi-service franchise platform.

I am contributing to the website design, application development, administrative workflows, database planning, cloud deployment and overall project management. The platform is being designed to support multiple GP clinic locations through a consistent and user-friendly digital experience.

The project also includes Google Workspace business email configuration, secure administrative access, cloud deployment on Google Cloud Platform and foundations for future AI-assisted patient enquiries, appointment support and healthcare administration workflows.

My responsibilities include requirements analysis, project planning, UI and UX coordination, backend planning, cloud infrastructure, workflow automation, testing and deployment management.

I am leading the planning and development of a transparent digital platform that allows donors to identify students’ educational needs and provide direct support for school supplies, technology, transportation, tuition and other essential learning requirements.

The platform is being designed with donor and administrator dashboards, student-support workflows, contribution tracking, email notifications and follow-up processes involving authorised school representatives. Its purpose is to improve transparency, accountability and communication between donors, students, schools and administrators.

My responsibilities include project planning, requirements analysis, platform design, software development coordination, workflow design, stakeholder engagement, testing and long-term expansion planning. The initiative is currently under development, with future plans to extend its support internationally.

The evaluation examined the research methodology, medical imaging workflow, feature extraction and dimensionality reduction methods, machine learning model selection, performance metrics, validation approach, dataset limitations and clinical relevance.

I assessed the use of Principal Component Analysis for reducing high-dimensional MRI features and reviewed the effectiveness of different machine learning algorithms for prostate cancer classification. I also provided recommendations to improve model validation, explainability, reproducibility, data quality and clinical reliability.

This project strengthened the connection between artificial intelligence, medical imaging, statistical analysis and evidence-based healthcare research.

I am contributing to the research design and development of methods for joint atomic clock error estimation, GNSS uncertainty prediction and robust positioning using signals from multiple satellite navigation systems.

The proposed approach combines mathematical modelling, statistical estimation, satellite signal data and machine learning to identify timing errors, predict positioning uncertainty and improve navigation performance under challenging environmental conditions.

My responsibilities include research planning, mathematical and statistical model development, machine learning methodology, uncertainty analysis, data-processing workflow design, model evaluation and technical documentation.

The research has potential applications in autonomous vehicles, aviation, maritime navigation, logistics, surveying, emergency services and other safety-critical positioning systems.

I am contributing to the platform’s system design, healthcare workflows, data integration, security requirements and project management. The solution is being designed to support structured clinical information, role-based access control, emergency break-glass access, tamper-evident audit records and secure communication between authorised healthcare professionals.

The platform incorporates healthcare interoperability standards, including FHIR R4 and HL7, to support reliable data exchange with hospitals, clinics and other healthcare systems. It also establishes foundations for future AI-assisted clinical documentation, risk identification, workflow automation and decision support, with appropriate human oversight.

My responsibilities include requirements analysis, enterprise system design, healthcare data integration, security planning, workflow development, testing strategy, technical coordination and project delivery.

As the AI/ML Engineer, I designed and developed AI-enabled features to improve provider matching, job prioritisation, dispatch decision support, risk classification and exception handling. I contributed to human-in-the-loop approval workflows, ensuring that higher-risk or unusual cases could be reviewed before final action.

The platform includes customer, recovery provider, insurance and dispatch portals, together with operational dashboards, finance and invoicing workflows, marketplace matching and automated job coordination.

Key Skills: Artificial Intelligence, Machine Learning, Agentic AI, Multi-Agent Systems, Workflow Automation, Provider Matching, Dispatch Optimisation, Risk Classification, Human-in-the-Loop AI, Python, Cloud Platforms and Enterprise Software Development.