Xavier Adiyi

Design and development of an intelligent web application for generating custom orthopedic insoles from smartphone foot photos.

Development of computer vision models based on YOLOv8 for automatic detection of key foot points (toes, heel, arch) from lateral view images.

Implementation of a complete AI pipeline for biometric analysis: object detection, segmentation, extraction of precise measurements (length, arch height, etc.), and image processing using binary masks.

Design and deployment of the cloud architecture on AWS and GCP, including containerization with Docker and orchestration with Kubernetes.

Industrialization of ML workflows via CI/CD (GitHub Actions) for model training, evaluation, and deployment.

Direct collaboration with founders in an R&D-focused startup environment, at the intersection of AI, health, 3D manufacturing, and user experience.

I contributed to the development of the DibaCare healthcare platform used to manage hospital operations across doctors, patients, specialties, and schedules. I helped design and build both the web application (Next.js) and mobile app (Flutter), ensuring consistent UI/UX and reliable performance across devices. I worked collaboratively with a multidisciplinary team to maintain alignment between frontend workflows and backend functionality, and performed extensive integration testing to prepare the product for a successful MVP launch.

As part of the platform’s intelligent services, I also developed a Healthcare RAG Chatbot that supports medical FAQs and availability queries. This included designing a semantic search pipeline with OpenAI embeddings and a vector database, and implementing intent classification to route queries (FAQs, availability, consultations). I further extended the system with a basic medical triage capability and applied MLOps practices including CI/CD automation, modularization, and testing to ensure production readiness and operational reliability.

Within the Odoo ERP system, I contributed to the development of web applications designed to deliver a smooth and intuitive user experience. I designed and integrated features tailored to user needs while ensuring system consistency and performance.

In parallel, I participated in the development of robust backend applications using Node.js, improving the overall reliability, modularity, and performance of the system. These developments enhanced business process management and increased internal task automation.

I also deployed multiple containerized applications using Docker and Kubernetes on AWS, ensuring scalability, resilience, and easier infrastructure maintenance.

Finally, I implemented VPS (Virtual Private Server) solutions to enhance server performance, security, and availability, providing a stable and production-ready infrastructure.