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Muhammad A B Fayyaz

Senior Lecturer

Manchester Metropolitan University

United Kingdom

Research Interests

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About

Muhammad A B Fayyaz is a Lecturer at Manchester Metropolitan University in the United Kingdom. His research interests include big data analytics in healthcare, multimodal humanoid systems, machine learning for photovoltaic systems, and data security in vehicular networks. He has published recent articles on topics such as explainable video identification and innovative approaches to energy management in non-domestic buildings.

Articles (16)

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2026

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2020

Collaborators (2)

Mohammed Albekairi

Associate Professor

jouf university

SAUDI ARABIA

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Aris-Christos Alexoulis-Chrysovergis

Senior Lecturer

Manchester Metropolitan University

UNITED KINGDOM

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Muhammad A B Fayyaz

Research Interests

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Articles (16)

Fast and efficient motion planning: using hybrid sampling and simulated annealing

The Role of Big Data Analytics in Revolutionizing Diabetes Management and Healthcare Decision-Making

Transparent and trustworthy CyberSecurity: an XAI-integrated big data framework for phishing attack detection

Explainable AI-driven depression detection from social media using natural language processing and black box machine learning models

Weakly-Supervised Chromosome Segmentation via SAM and Uncertainty-Guided Pseudo-Labeling

Selecting Loss-Function for Unseen (Out-of-Distribution) Action Recognition in Videos

A Comprehensive Multimodal Humanoid System for Personality Assessment Based on the Big Five Model

Optimizing Large-Scale PV Systems with Machine Learning: A Neuro-Fuzzy MPPT Control for PSCs with Uncertainties

Design of an EnergyPlus Model-Based Smart Controller for Maintaining Thermal Comfortable Environment in Non-Domestic Building

Explainable YouTube Video Identification Using Sufficient Input Subsets

Blockchain enabled data security in vehicular networks

E-Ensemble: A Novel Ensemble Classifier for Encrypted Video Identification

A CPW fed quad-port MIMO DRA for sub-6 GHz 5G applications

SCNN-Attack: A Side-Channel Attack to Identify YouTube Videos in a VPN and Non-VPN Network Traffic

A review of the technological developments for interlocking at level crossing

Object Detection at Level Crossing Using Deep Learning

Collaborators (2)

Mohammed Albekairi

Aris-Christos Alexoulis-Chrysovergis

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