Research output per year
Research output per year
Dr
University of Huddersfield
Queensgate
Huddersfield
HD1 3DH
United Kingdom
Accepting PhD Students
PhD projects
Adversarial Machine Learning. Machine Learning for Intelligent threat detection, attack modelling. Agentic AI for security automation.
Research activity per year
Dr Samuel Onidare is a Lecturer in Computer Networks and Distributed Systems at the University of Huddersfield. His research focuses on the integration of artificial intelligence and machine learning with cybersecurity and wireless communication systems.
His work explores the application of machine learning for intelligent threat detection, attack modelling, and security automation, with a particular emphasis on securing modern and future networked systems. In parallel, he investigates the use of machine learning for wireless resource allocation and optimisation, addressing challenges in spectrum efficiency, interference management, and adaptive network control.
A key theme of his research lies at the intersection of wireless communications, cybersecurity, and machine learning, where data‑driven methods are used to jointly enhance performance, resilience, and security in complex communication environments. His interests span intelligent networking, secure wireless systems, and applied machine learning for next‑generation communication infrastructures.
PhD, On the efficiency of dynamic licensed shared access for 5G/6G wireless communications, Lancaster University
1 Oct 2016 → 19 Apr 2021
Award Date: 10 Jun 2021
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review