MS Computer Systems Engineering | AI & ML Researcher
Computer Systems Engineer specializing in secure federated learning, large language models, and next-generation wireless networks. Passionate about advancing distributed AI security through rigorous doctoral research.
Researcher. Educator. Lifelong Learner.
I am a dedicated researcher in Computer Systems with a strong foundation in machine learning, deep learning, mobile and wireless networks, IoTs and distributed systems security.
Currently serving as a Secondary School Teacher for IT (E&SED) while actively pursuing advanced research collaborations. I have published in reputable venues including Elsevier Array and MDPI Electronics, with additional works under review at IEEE Transactions.
I am proficient in Python, TensorFlow, and federated learning frameworks, mobile networks, network security, cloud computing, and academic research methodologies. I am fluent in English (C2), Urdu, and Pashto.
Areas of expertise and active investigation
Secure aggregation, Byzantine-robust optimization, and privacy-preserving distributed learning for resource-constrained devices.
Fine-tuning LLMs for cybersecurity applications, automated threat detection, and hyperparameter optimization in FL.
Intrusion detection systems, model poisoning defense, blockchain-enhanced security for V2X and IoVT networks.
5G/6G network optimization, SINR prediction, wireless sensor networks, and mobile network security.
Explainable AI frameworks integrated with blockchain for transparent and trustworthy security systems.
Content filtering, computer vision, and signal processing using advanced neural network architectures.
Peer-reviewed journals and conference proceedings
Internet of Things, Vol. 39, September 2026, 102047
Array, Vol. 28, December 2025, 100520
Electronics, Vol. 9, Issue 10, 1660
World Transport Convention (WTC 2026)
SSRN Electronic Journal
Research Square
Academic background and qualifications
Professional and research experience
Current and completed research initiatives
Currently under review at IEEE Transactions on Consumer Electronics. Fine-tuning LLMs to detect and mitigate model poisoning attacks in federated IoT systems.
Status: Under ReviewResearch on securing Internet of Vehicles Things using advanced aggregation techniques. Currently under review at IEEE Transactions on Vehicular Technology.
Status: Under ReviewExperimental framework using large language models to automate and optimize federated learning hyperparameters for improved convergence and security.
Status: In ProgressImplemented and validated a dual-aggregation approach to fortify federated learning against poisoning attacks in IoT environments. Published in Elsevier Array.
Status: PublishedMS thesis project developing machine learning models for Signal-to-Interference-plus-Noise Ratio prediction in 5G networks. Published in MDPI Electronics.
Status: PublishedCloud computing project utilizing AWS Comprehend for real-time sentiment analysis of Twitter data during MS studies.
Status: CompletedTools, technologies, and competencies
Professional development and specialized training
IBM through Coursera
University of Michigan through Coursera
University of Michigan through Coursera
Interested in collaboration or PhD supervision? Let's connect.
ruzzatullah@gmail.com
Connect professionally
0000-0002-3400-1357
Follow my research
+92 343 9451362
Karak, Khyber Pakhtunkhwa, Pakistan