Marwan Mohammed

• Engineered and implemented deep reinforcement learning algorithms to optimize traffic systems. • Designed and developed simulation environments to validate models, fine-tuning parameters for real-world deployment. • Led the integration of quantum annealing with deep learning for traffic optimization, ensuring successful real-world application. • Verified and validated system performance, ensuring robustness and efficiency in real-world scenarios.

• Applied deep reinforcement learning to robotic manipulation, developing algorithms for optimized grasping and handling. • Developed deep reinforcement learning algorithms combined with color matching-based robotic manipulation using semantic segmentation. • Fused data from dual RGB-D cameras to enhance robotic vision and accuracy. • Designed simulations and integrated them with real-world robotic hardware. • Designed and built a 3D-printed humanoid robotic arm with real-time control algorithms.

• Designed and simulated motion control algorithms for a robotic exoskeleton aimed at supporting lower-limb mobility. • Collected and refined motion data using IMUs and EMG sensors for improved model training. • Deployed control algorithms in rehabilitation trials, enhancing the system’s adaptability and responsiveness.

• Designed and implemented electrical circuit diagrams for security systems (CCTV, alarms, barrier gates, magnetic door systems). • Installed and configured security hardware and software, ensuring functionality and system integration. • Troubleshot and optimized technical issues, increasing system reliability and security compliance.

I hold a Master of Science in Mechatronics Engineering with a focus on designing robotic control systems for lower-limb-assisting robotic exoskeletons and robotic motion control.