AI Researcher & Network Security Enthusiast

Muhammad Zamad Qureshi

Researcher

Passionate researcher specializing in Federated Learning, Reinforcement Learning, AI-enabled Network Security, IoT Security, and 6G Networks.

Currently implementing Privacy-Preserving Federated Learning using the Flower Framework for intelligent intrusion detection systems.

2+

Research Publications

8+

Technical Skills

4+

Networking Tools

AI

Research & Innovation

Who Am I?

About Me

Hello! I'm Muhammad Zamad Qureshi, a passionate researcher with strong interests in Artificial Intelligence, Federated Learning, Reinforcement Learning, IoT Security, Network Security and AI-enabled 6G Networks.


My current research focuses on implementing Privacy-Preserving Federated Learning using the Flower Framework for intelligent intrusion detection systems. I enjoy solving real-world cybersecurity challenges through Artificial Intelligence and distributed machine learning.


Alongside my research, I possess practical experience in network simulation, protocol analysis, traffic monitoring and networking tools including OMNeT++, NS3, Cisco Packet Tracer, and Wireshark.

Academic Journey

Education

Master of Science (MS) in Information Technology

The Islamia University of Bahawalpur

Specialized in Artificial Intelligence, Machine Learning, Cyber Security, Networking and Research Methodologies.

Bachelor of Science (BS) in Information Technology

Government College University Faisalabad

Built a strong foundation in programming, databases, networking, software engineering, web development, and operating systems.

Areas of Interest

Research Interests

Machine Learning

Deep Learning

Federated Learning

Reinforcement Learning

AI Network Security

IoT Security

SDN + Satellite + 6G Networks

Flower Framework

Professional Expertise

Technical Skills

Python 95%
HTML 90%
CSS 88%
JavaScript 80%
Cisco Packet Tracer 95%
Wireshark 90%
OMNeT++ 92%
NS3 88%
Featured Work

Projects

Privacy-Preserving Federated Learning

Developing an intelligent intrusion detection framework using the Flower Framework for Privacy-Preserving Federated Learning in IoT-enabled environments.

AI-Based Network Security

Research focused on AI-enabled Network Security, Reinforcement Learning, Privacy Preservation and secure communication for future intelligent networks.

Network Simulation & Analysis

Practical experience with OMNeT++, NS3, Cisco Packet Tracer, and Wireshark for network simulation, protocol analysis, and performance evaluation.

Research Contributions

Publications

Published

IoT Intrusion Detection with Deep Learning Techniques

Published research focusing on Deep Learning based intrusion detection techniques for Internet of Things environments.

View Publication
Published

Revolutionizing Retail Automation through Human-Object Interaction Detection

Research focused on intelligent retail automation using Artificial Intelligence and Human-Object Interaction Detection.

View Publication
Developer Corner

Random Developer Joke

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Let's Connect

Contact Me

Phone

+92 309 7021181