Amr Ahmed

Developed advanced acoustic simulation and signal processing frameworks for sound source localization in complex urban environments. Applied machine learning, deep neural networks, and beamforming algorithms to large-scale audio datasets for robust spatial estimation. Deployed end-to-end ML pipelines for embedded and cloud inference, integrating multi-sensor fusion (audio, IMU) for ADAS, robotics, and structural health monitoring applications.

Collaborated with global OEMs and engineering partners on electric vehicle development, focusing on battery systems, supplier qualification, and market intelligence. Delivered machine learning tools and data-driven insights to support strategic decisions, while aligning cross-functional teams with business objectives and KPIs.

Delivered hardware–software integration for interactive systems in the pharmaceutical marketing sector, developing microcontroller-based control solutions and embedded electronics. Programmed in Embedded C and Python to interface sensors, actuators, and displays for real-time user interaction at international exhibitions.

Master Thesis: "Automotive Acoustic Simulation and Siren Signal Localization" - Developed a comprehensive hybrid simulation framework for sound source localization in complex acoustic environments, incorporating source-time dominant propagation modeling, reverberation effects, Doppler effect modeling, and advanced beamforming algorithms. Validated framework against real measurements with successful implementation of deep neural networks for spatial parameter estimation.

Grade: 3.4 (excellent) Skills: Control Systems · Control Systems Design · Digital Signal Processing · Signal Processing · Programmable Logic Controller (PLC) · Microcontrollers · Mobile Robotics · C (Programming Language) · Embedded C · Embedded Systems · Sensors · Computational Fluid Dynamics (CFD) · Computer Numerical Control (CNC) · Mechanical Engineering