Muhammad Saad Farooq

PROFESSIONAL PROFILE Final-year undergraduate Electrical Engineering student at NUST with strong interests in RTL design, computer architecture, embedded systems, FPGA-based design, and AI accelerators. Experienced in Verilog-based digital design, FPGA development, and machine learning through hands-on internships and academic projects. Seeking opportunities to apply hardware–software co-design, AI acceleration, and digital system design skills in research-oriented or industry environments. EDUCATION Bachelors Electrical Engineering School of Electrical Engineering & Computer Sciences , Islamabad (2026) INTERNSHIP EXPERIENCE National Engineering Complex of Pakistan 24-Jun-2025 - 23-Nov-2025 Designed and verified combinational and sequential digital circuits (logic gates, flip-flops, FSMs) using Verilog, strengthening RTL design and verification skills. Developed FPGA-based projects using Xilinx Vivado IPs and prepared structured documentation and presentations explaining design flow and functionality. Integrated and tested communication protocols including I2C, SPI, and UART, gaining hands-on debugging and interfacing experience. Improved design efficiency and reliability through modular coding practices and systematic testing. Machine Learning Intern – Digital Empowerment Pakistan 05-Feb-2023 - 06-Mar-2023 Gained practical experience in AI, Machine Learning, Deep Learning, CNNs, and image processing. Worked with PyTorch, TensorFlow, and Google Colab for model development and optimization. Used Python for data preprocessing and image analysis tasks. FINAL YEAR PROJECT High-Speed AI Accelerator for Real-Time Applications Designing and implementing an FPGA-based AI accelerator on the Xilinx ZCU102 platform for real-time deep learning workloads. Optimizing convolution layers and MAC processing elements using a systolic array architecture to achieve high throughput and low latency. Evaluating accelerator performance against CPU/GPU implementations in terms of speedup, resource utilization, and accuracy. Targeting real-time deployment of vision-based AI models such as YOLOv8. Tools & Technologies: Verilog HDL, Xilinx Vivado, ZCU102 FPGA, AI/ML Models TECHNICAL EXPERTISE RTL & FPGA Design RTL Design, Verilog HDL, SystemVerilog, Computer Architecture, RISC-V Processor Design, Digital System Design, Hardware Verification, AXI Interface, Systolic Array Architecture, FPGA Implementation Embedded Systems Embedded C, Microcontroller Programming, GPIO & Peripheral Interfacing, I2C, SPI, UART Microcontrollers: Arduino, ATmega328P, ATmega16A, STM32, ESP32 Tools: Arduino IDE, Atmel Studio, STM32CubeIDE

Final-year undergraduate Electrical Engineering student at NUST with strong interests in RTL design, computer architecture, embedded systems, FPGA-based design, and AI accelerators. Experienced in Verilog-based digital design, FPGA development, and machine learning through hands-on internships and academic projects. Seeking opportunities to apply hardware–software co-design, AI acceleration, and digital system design skills in research-oriented or industry environments.