Muhammad Saad Kashif

PROFESSIONAL PROFILE Electrical Engineering graduate with hands-on experience across industrial automation, power systems, and advanced networking technologies. Proven exposure to PLCs, VFDs, transformer manufacturing, and tender documentation, complemented by strong skills in Linux-based development, Deep Packet Inspection (DPI), SDN, and AI-driven security systems. Experienced in real-world industrial and research projects, including edge-based DPI on Raspberry Pi and AI-powered KYC systems. Adept at bridging hardware and software domains, with strong analytical, communication, and problem-solving skills. Seeking to contribute to technology-driven engineering and networking environments. EDUCATION Bachelors of Electrical Engineering School of Electrical Engineering and Computer Science , Islamabad , 2.55 (2026) INTERNSHIP EXPERIENCE D.G Cement Company Ltd, Dera Ghazi Khan. 09-Jun-2023 - 23-Jul-2023 Worked at Air-Cooled Condensed Project (Installed at WHR). • PLC Programming and Distributed Control System (DCS) Panels. • Variable Frequency Drives (VFDs) and Motors. • Process of Coal-Fired Power Plant (CFPP). • Field Instruments. Creative Group of Companies, Township, Lahore. 24-Jun-2024 - 24-Aug-2024 Worked at Transformer Manufacturing Section & at sales & marketing department. • Transformer manufacturing. • Core and Windings. • Working on Tender requests and kept records of tenders. • Compiling biding documents for Tenders. xFlow Research,I-9/3, Islamabad. 01-Jul-2025 - 25-Jan-2026 • Researched on a variety of commercial AI tools and learned to use them on industrial projects. • Developed an AI automated 2-step KYC self-verification module with facial verification, deepfake and liveness detection, OFAC and UN sanction filtering. • Researched on various international messaging and calling tools, and learned to use tools like Twilio. • Learned about and implemented secure gateways, application stress testing, API development, etc. • Overall learned a variety of industrial-significant skills and gained hands- on experience on real-life industrial company projects. FINAL YEAR PROJECT Edge DPI on Raspberry Pi for Real-Time Anomaly Detection in SDN-Enabled IWSNs This final year project (FYP) focuses on developing a AI-driven Deep Packet Inspection (DPI) system for real-time anomaly detection in Industrial Wireless Sensor Networks (IWSNs) integrated with Software-Defined Networking (SDN). IWSNs are critical for industrial automation but vulnerable to cyber threats and failures. The project incorporates federated learning, utilizing Raspberry Pi devices as nodes, where each node hosts a local AI model and DPDK-accelerated DPI engine, connected to a centralized server for global model aggregation. This enhances detection of known and unknown anomalies while optimizing resource use in constrained environments. The system integrates with SDN for dynamic policy enforcement, improving resilience, adaptability, and threat mitigation in industrial settings. TECHNICAL EXPERTISE

Electrical Engineering graduate with hands-on experience across industrial automation, power systems, and advanced networking technologies. Proven exposure to PLCs, VFDs, transformer manufacturing, and tender documentation, complemented by strong skills in Linux-based development, Deep Packet Inspection (DPI), SDN, and AI-driven security systems. Experienced in real-world industrial and research projects, including edge-based DPI on Raspberry Pi and AI-powered KYC systems. Adept at bridging hardware and software domains, with strong analytical, communication, and problem-solving skills. Seeking to contribute to technology-driven engineering and networking environments.