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Schedule Interview NowMy name is Muhammad Ahmad B. and I have over 0 years of experience in the tech industry. I specialize in the following technologies: Compliance, Information Security, Cyber Threat Intelligence, Cybersecurity Management, Cybersecurity Monitoring, etc.. I hold a degree in Doctor of Philosophy (PhD), Master of Science (MS), Bachelor of Science (BS). Some of the notable projects I've worked on include: Transformer and GNN FL for Cellular Traffic Prediction, FL With Explainable AI for Malicious Traffic Detection in IoT Networks, PB-DID for DoS and DDoS Attacks Using UNSW-NB15 and Bot-IoT Data-Sets, ID in IoT, using ML based on TCP layer features (UNSW-NB15 data-set). I am based in Islamabad, Pakistan. I've successfully completed 4 projects while developing at Softaims.
I approach every technical challenge with a mindset geared toward engineering excellence and robust solution architecture. I thrive on translating complex business requirements into elegant, efficient, and maintainable outputs. My expertise lies in diagnosing and optimizing system performance, ensuring that the deliverables are fast, reliable, and future-proof.
The core of my work involves adopting best practices and a disciplined methodology, focusing on meticulous planning and thorough verification. I believe that sustainable solution development requires discipline and a deep commitment to quality from inception to deployment. At Softaims, I leverage these skills daily to build resilient systems that stand the test of time.
I am dedicated to making a tangible difference in client success. I prioritize clear communication and transparency throughout the development lifecycle to ensure every deliverable exceeds expectations.
Main technologies
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Government of Pakistan
Mobile traffic prediction is essential for efficient 5G/6G network management. Studied FL for privacy-preserving cellular traffic forecasting, evaluating recurrent models, attention mechanisms, Transf
The rapid growth of IoT devices demands scalable, privacy-preserving, and interpretable intrusion detection systems. This work proposes an IDS combining Federated Learning (FL) and Explainable AI (XAI
Since its inception, the Internet of Things (IoT) has grown rapidly, enabling automation through the integration of devices and data. While transforming businesses and society, IoT also faces increasi
IoT networks generate continuous data exchanges, making data security a critical challenge. Due to the low-power nature of IoT devices, Network Intrusion Detection Systems are commonly used to filter
Doctor of Philosophy (PhD) in
2023-01-01-2026-01-01
Master of Science (MS) in
2018-01-01-2020-01-01
Bachelor of Science (BS) in
2012-01-01-2016-01-01