Bilal Rafique

Summary

Bilal Rafique is a visionary researcher and software engineer with a Bachelor’s degree in Software Engineering from Mirpur University of Science and Technology, Pakistan, and a Master’s degree in Software Engineering from Southwest University of Science and Technology, China. He is currently pursuing a PhD in Information and Control Engineering at the same university, focusing on cybersecurity and artificial intelligence. With more than four years of professional experience in web development, Bilal blends industry expertise with academic research to address modern challenges in network security, web security, smart grids, recommendation systems, and medical image privacy.

He has authored several impactful publications, including “An Enhanced Integrated Fuzzy Logic-Based Deep Learning Techniques (EIFL-DL) for the Recommendation System on Industrial Applications” in PeerJ Computer Science and “Enhanced Cybersecurity for Smart Grids: Detecting Protocol-Specific DDoS Attacks on Modbus Networks” in Elsevier’s Computers and Electrical Engineering. His earlier work also includes “Understanding Public Opinions on Social Media About ChatGPT – A Deep Learning Approach for Sentiment Analysis.” In addition, his recent paper “Network Attack Detection on Balanced Dataset Using Shallow and Deep Neural Networks” has been accepted for presentation at the IEEE-sponsored DSIS 2025 International Conference on Data Science and Intelligent Systems.

Passionate about pushing the boundaries of AI-driven security systems, Bilal aims to develop innovative, scalable, and trustworthy solutions to strengthen cyber-physical infrastructures and safeguard the digital world.

Algorithms & Analysis of Algorithms Artificial Intelligence Internet of Things Neural Networks Sentiment Analysis