Open to opportunities

Akinsola Timileyin

@akinsolatimileyin

Message

I build machine learning image-classification pipelines and full-stack Flask applications.

Nigeria

Message

What I'm looking for

I'm looking for an entry-level machine learning, computer vision, or full-stack development role where I can build practical systems, analyze technical data, write clear documentation, and grow through independent, deadline-driven work.

I'm developing an automated wood plank surface-classification system at Olabisi Onabanjo University using a hybrid ResNet-50, PCA, and Decision Tree pipeline on the VNWoodKnot dataset.

My research combines image-based data interpretation, model evaluation, and rigorous technical writing. I've also audited a five-chapter academic document against peer-reviewed sources from Springer, ScienceDirect, MDPI, and IEEE Access to support factual accuracy.

Alongside my thesis, I've built and deployed four Flask applications—a Blog/CMS, Library Management System, Task Manager, and Expense Tracker—with authentication, CRUD functionality, SQLite databases, and technical documentation.

Experience

Work history, roles, and key accomplishments

Current

Flask Portfolio Application Suite

Current

Personal Projects

Jan 2025 - Present (1 year 7 months)

Built and deployed four full-stack web applications using Flask, SQLite, and SQL schema design. Implemented user authentication, CRUD functionality, and relational database design.

Flask SQLite SQL Python HTML CSS Git GitHub CRUD Authentication

Undergraduate Thesis Researcher

Olabisi Onabanjo University

Jan 2025 - Jan 2026 (1 year)

Designed a hybrid CNN–Decision Tree image classification pipeline for wood plank surface defect classification. Conducted literature audits and produced structured technical write-ups.

CNN PCA Decision Trees scikit learn Model Evaluation literature review