Robert Akinie's Portfolio

Projects

Federated Learning based Intrusion Detection Systems for Transportation IoT

This repository represents a basic implementation for the corresponding research paper, Fine-Tuning Federated Learning-based Intrusion Detection Systems for Transportation IoT.

GitHub Repo

Capstone Project

End-to-end development of a smart self-sorting recycliny system (trash can), impleented with convolutional nets and ladder logic programming.

GitHub Repo

CSE 708: Data Analytics and Engineering

The scope of this project is on an end-to-end predictive modeling machine learning problem, with the application on binary classification, on the Census Income dataset, extracted from the US Adult Census bureau database, and the primary problem is a prediction task: determining whether a person from the Census database made over $50, 000 a year.

GitHub Repo

Google Scholar

Check out my research publications on Google Scholar.

Google Scholar Profile

Blogs

Read my latest thoughts and lessons on my machine learning and AI experiences.

An Unexpected Realization on Principal Component Analysis

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Research Papers

Finetuning Federated Learning-based Intrusion Detection Systems for Transportation IoT

Accepted in IEEE SoutheastCon 2025.

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NCAT12-DET: A New Benchmark Dataset for Surface Defect Detection and a Comparative Study

Published in IEEE Access, co-author

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About Me

I'm Robert Akinie, a doctoral student pursuing an Electrical/Computer Engineering degree from North Carolina A&T State University. I received the B.S. degree in Electrical and Computer Engineering from Calvin University in 2021. My research interests include anomaly and intrusion detection systems, perceptual uncertainty in autonomous vehicles, autonomous vehicle architecture, and federated learning for IoT applications. .