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Oluwaseun Ilori Photo

Oluwaseun Ilori

MSc Computer Science (AI)Data Scientist at MyLane.AIComputer Vision EngineerNatural Language Processing

Applied AI for research and real-world systems

Data Scientist and AI Engineer building practical systems for real-world problems.

I hold an MSc in Computer Science with an AI specialization and currently work as a Data Scientist at MyLane.AI. My work spans labor market analytics, computer vision systems, OCR pipelines, natural language processing, explainable AI, and research-driven product delivery.

Data ScienceComputer VisionNatural Language ProcessingExplainable AIForecastingMLOps & Deployment

About

Data scientist and AI engineer with a strong mix of research, analytics, and delivery experience.

I build systems and analysis workflows that connect data collection, modeling, experimentation, and deployment. My interests span data science, computer vision, NLP, forecasting, and practical machine learning for real-world problems.

Education: MSc Computer Science (AI specialization), Babcock University. B.Eng Electrical and Electronics Engineering, University of Uyo.

Research interests: Computer Vision, Edge AI, Machine Learning, and Explainable AI.

Data science and analytics

My work includes labor market analysis, forecasting, compensation parsing, data cleaning, and turning raw data into reporting-ready outputs for decision making.

Computer vision and NLP

I work across computer vision and natural language processing, building systems for detection, OCR, image understanding, and language-driven data workflows.

Data and ML systems

I build end-to-end systems that go from data collection and validation to modeling, storage, cloud workflows, APIs, and analytics dashboards.

Research and teaching

Alongside hands-on engineering, I contribute through research, tutoring, SQL practicals, machine learning instruction, Linux system administration, and technical mentorship.

Experience

Recent roles across data science, computer vision, teaching, and applied research.

My background combines experimentation, production delivery, and technical communication. I work best on teams where insight quality matters as much as implementation quality.

Selected wins

  • Won the 2022 MathWorks MiniDrone Competition virtual round in the EMEA region, finishing ahead of 330+ teams.
  • Published research spanning malaria detection, explainable AI in healthcare, and smart surveillance systems.
  • Designed systems across diagnostics, OCR, object detection, segmentation, and forecasting.

MyLane.AI

Jul 2024 - Present

Data Scientist

  • Analyze U.S. labor market trends using job postings data, BLS, and Census sources.
  • Build forecasting models for workforce growth across healthcare specialties.
  • Support compensation parsing systems for wage extraction and normalization.

TalaNanu

May 2023 - Jun 2024

Computer Vision Engineer

  • Trained and deployed a fine-grained image classifier that reached 98% accuracy.
  • Reduced OCR inference latency from over one minute to under 20 seconds.
  • Delivered model training and deployment workflows with Docker, FastAPI, and GCP.

Babcock University

Oct 2025 - Present

Teaching Assistant and E-Tutor

  • Teach machine learning, Linux system administration, C programming, and data management.
  • Lead practical SQL sessions for Database Systems Design, Implementation and Management.

Zummit Africa

Nov 2021 - Mar 2022

Deep Learning Intern

  • Led an emotion detection project from predictive modeling through deployment.
  • Supported team members who were new to deep learning workflows.

Skills

Tools and technologies I have used across data science, NLP, computer vision, and deployment.

My work spans analytics, modeling, NLP, computer vision, and deployment, using tools that support both research and production delivery.

Coverage

Data analysis, forecasting, NLP, computer vision, APIs, cloud deployment, and research workflows.

Programming and Data

PythonPostgreSQLMATLAB/SimulinkNumPyPandasStatsmodelsProphetParquetWeb ScrapingScrapy

Machine Learning and AI

PyTorchTensorFlowKerasScikit-learnOpenCVspaCyNLTKGensim

MLOps and Cloud

MLflowDockerFastAPIGitGoogle Cloud PlatformGoogle Cloud StorageBigQueryAirflowdbtPoetryAzure ML Studio

Analytics and Visualization

Looker StudioMatplotlibPlotlyEDAForecastingCompensation Parsing

Selected Projects

Projects grouped by capability area so data work and computer vision work are easy to scan separately.

The portfolio is organized to show the range of my work across analytics engineering, data pipelines, and computer vision systems.

Focus Areas

Data science, analytics pipelines, computer vision, OCR, and deployment workflows.

Data Science

Supermart NG Price Tracker

Supermart NG Price Tracker

Built a retail price tracking pipeline that scrapes Supermart product pages, cleans and validates product records, prepares analytics-ready datasets, and supports reporting with Google Cloud Storage, BigQuery, dbt, and Airflow.

View project

Computer Vision and Applied Machine Learning

Aerial Semantic Segmentation

Aerial Semantic Segmentation

Built a semantic segmentation workflow for aerial imagery, combining custom OpenCV augmentation with a MobileNetV3-small U-Net architecture for low-data training.

View project
Malaria Parasite Detector

Malaria Parasite Detector

Trained an object detection system to count malaria parasites and white blood cells, then packaged prediction behind a custom FastAPI service deployed with Docker on Google Cloud.

View project
License Plate Reader and Custom OCR

License Plate Reader and Custom OCR

Built the full ANPR pipeline for Nigerian plates, from data preparation and annotation tooling to object detection, custom OCR, and threshold adjustment with a regression model.

View project
Face Recognition and Tracking

Face Recognition and Tracking

Developed a real-time face recognition workflow with multi-object tracking for continuous identity matching in video streams.

View project
Monocular Depth Estimation

Monocular Depth Estimation

Implemented a custom ResNet18 encoder-decoder with skip connections for monocular depth estimation and trained it on the NYU-v2 dataset.

View project

Publications

Research outputs that reflect my interest in trustworthy computer vision and applied AI.

My published work covers malaria detection, explainable AI in healthcare, and embedded surveillance systems.

Research themes

Computer vision, explainability, healthcare AI, and intelligent sensing systems.

Selected publications

Performance Evaluation of YOLOv12 Models for Malaria Parasite and White Blood Cell Detection

Performance Evaluation of YOLOv12 Models for Malaria Parasite and White Blood Cell Detection

Peer-reviewed study evaluating YOLOv12 variants for malaria microscopy detection, with emphasis on robust counting performance and practical diagnosis support.

View project
Explainable AI: A Systematic Literature Review Focusing on Healthcare

Explainable AI: A Systematic Literature Review Focusing on Healthcare

Systematic review of explainable AI methods in healthcare, covering interpretability trends, adoption concerns, and opportunities for trustworthy ML systems.

View project
Design and Implementation of a Smart Surveillance System

Design and Implementation of a Smart Surveillance System

Engineering paper describing a Raspberry Pi-based surveillance system that combines sensing, RFID validation, and automated alerts for rapid incident response.

View project

Blog Posts

Technical writing on computer vision, deployment, and machine learning workflows.

I also write about ideas, experiments, and implementation details from projects I have worked on.

Topics

Image classification, OCR, OpenCV applications, and deployment workflows.

Selected writing

Beyond RGB in Image Classification

Beyond RGB in Image Classification

A look at how different color spaces and normalization choices can affect image classification performance.

View project
Deploying OpenCV Web Application on Heroku

Deploying OpenCV Web Application on Heroku

A practical guide to deploying an OpenCV-powered web application and handling the packaging details.

View project
Custom OCR

Custom OCR

A breakdown of how I built a custom OCR pipeline for license plate recognition with machine learning.

View project

Certifications

Courses and certifications that have shaped my technical background.

Here are some of the courses and training I have completed over the years.

Training areas

Deep learning, computer vision, machine learning fundamentals, and research writing.

Grant Writing Class

Jun 2025

Research, Innovation and International Cooperation, Babcock University

Training focused on proposal development, research communication, and funding readiness.

Deep Learning With PyTorch

Jan 2024

OpenCV.org

Practical deep learning training using PyTorch for model development and experimentation.

Convolutional Neural Networks in TensorFlow

Oct 2021

DeepLearning.AI

Applied CNN concepts, image workflows, and TensorFlow-based deep learning implementation.

Introduction to AI, ML and DL

Sep 2021

DeepLearning.AI

Foundational overview of artificial intelligence, machine learning, and deep learning systems.

Machine Learning with Python

Jul 2020

CognitiveClass.ai

Introductory machine learning coursework covering core concepts and Python-based workflows.

Computer Vision for Faces

Oct 2018

Big Vision LLC / LearnOpenCV

Covered image processing, OpenCV, Dlib, machine learning, and face recognition system development.