Muhammad Shahbaz
Saudi Data & AI Authority (SDAIA)
Riyadh, Saudi Arabia
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This is Muhammad Shahbaz, a Senior Solution Architect and Cybersecurity Advisor with 16 years of experience AI, ML, DL, data science transformation and securing IT infrastructures across enterprises, banks, hospitals, and government sectors in Saudi Arabia. I have contributed to modernizing national datacenters, cloud adoption strategies, and cybersecurity frameworks, playing a key role in digital transformation programs aligned with Saudi Vision 2030. My expertise includes designing and securing high-performance infrastructure platforms, implementing advanced network architectures, and deploying automation solutions to enhance resilience and efficiency in AI-enhanced datacenters. In cybersecurity, I have developed governance frameworks, enforced NCA and ISO-aligned standards, performed assessments, and implemented strong data protection measures. My contributions include authoring multiple AI and cybersecurity publications, conducting threat-hunting campaigns, building attack-and-restore simulations, and delivering AI-driven Google projects, including deployments with the Google team in London. These efforts strengthened defenses for national projects including Tawakkalna, SDAIA DEEM Cloud, NCA, the National Data Platform, and the National Data Bank, advancing Saudi Arabia’s vision 2030 digital ecosystem and cybersecurity posture.
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Smart GPU Interconnects: Leveraging AI/ML for Next-Gen Data Centres and Cloud Infrastructure
The modern data centers increasingly rely on GPUs to handle highly demanding workloads, including AI processing, large-scale simulations, and big data analytics. As the scale and complexity of these workloads grow, managing the communication between GPUs—known as GPU interconnects—becomes a critical challenge. Efficient data flow across GPUs is essential to maintaining performance and minimizing latency for computationally intensive applications.
Artificial intelligence and machine learning offer a powerful solution to this challenge. By analyzing GPU traffic patterns and predicting optimal data paths, AI-driven systems can dynamically optimize interconnect performance, reduce delays, and ensure smooth operation of complex applications. These systems are capable of making real-time adjustments autonomously, significantly reducing the need for manual intervention and increasing operational efficiency.
The benefits of leveraging AI/ML for GPU interconnects are substantial. Resource utilization is improved, workloads can scale seamlessly, and computing environments become faster, more reliable, and highly resilient. Smart GPU interconnects represent a transformative advancement, enabling next-generation workloads to run efficiently in both data centers and cloud infrastructures. This approach not only enhances technical performance but also establishes a foundation for future innovation in high-performance computing.
Data security and compliance for national interest
Expert in driving Digital Transformation and implementing strategic frameworks across Saudi industries, leveraging Microsoft technologies for innovation. Skilled in preparing organizations for compliance with regulatory authorities. Focused on aligning technology, governance, and industry standards for sustainable growth.
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