EMMANUEL OLUWASEGUN ADEYEYE

Led comprehensive research and engineering initiatives for SYNAPSE, a desktop platform combining real-time computer vision (YOLOv8, ONNX) with BIM deviation detection (ICP point cloud registration, IfcOpenShell, xeokit).

Owned the full-stack development, including ML pipeline design, 3D geometry processing, back-end architecture (Fast-API, Celery, Redis, Neo4j), and cross-platform distribution across Windows, macOS, and Linux.

Drove product strategy, data acquisition partnerships, and go-to-market efforts across construction, mining, and oil & gas verticals, expanding market reach and adoption.

Trained and evaluated diverse AI models using high-quality annotated datasets, significantly improving model performance and reliability.

Reviewed AI-generated responses for accuracy, relevance, and factual consistency, ensuring data integrity across various projects.

Developed and applied comprehensive annotation guidelines to ensure consistent training data, streamlining data preparation processes.

Labeled and validated extensive text, image, and multi-modal data, directly supporting the development and refinement of machine learning applications.

Led development of automated data pipelines using Python and SQL Server, integrating 100+ datasets and improving model-ready data quality by 20%.

Built Python-based analytical engines with real-time validation, drift detection, and anomaly flagging to support operational decision-making.

Developed desktop workflow tools using PySide/Qt, integrating early-stage computer vision outputs into operator dashboards.

Designed layered data models and backend frameworks (raw to validated to aggregated) to support scalable analytical and automation tools.

Strengthened C++ skills through performance-sensitive modules and integration required for real-time processing, enhancing system efficiency.

Designed and implemented analytical frameworks in Python and SQL, improving service accuracy by 30% and reducing manual processing by 25%.

Built cross-department dashboards and workflow tools supporting eight business areas, incorporating live metrics and exception-based logic.

Developed Python-based validation frameworks, schema checkers, and ingestion logic to integrate external data sources with internal systems.

Standardized data definitions and created dimensional models, reducing reporting friction and improving cross-team alignment.

Built back-end components and automated data pipelines in Python and SQL to support public service analytics.

Integrated external demographic and geographic datasets to support strategic planning and resource allocation.

Created a comprehensive data logic documentation system, enabling faster onboarding for technical teams.

Provided technical guidance to 50+ stakeholders, improving data literacy and workflow efficiency.

Entered data into Excel spreadsheets in the administrative office, ensuring accurate record-keeping.

Repaired hardware and carried out routine system maintenance, maintaining operational efficiency.

Supervised students during tests and examinations, ensuring smooth academic processes.

Developed a complete web page from scratch, including back-end services, front-end interface, and database using Django.

Built custom services to manage application state and facilitate communication with back-end APIs.

Repaired hardware and carried out routine system maintenance for the ICT department.

Developed a front-end webpage for the ICT department using HTML and CSS.