Amir is a Robotics and AI Engineer with a strong academic and practical background in Electronics, Control Systems, AI, and intelligent Robotic Systems. His expertise lies in integrating machine learning, computer vision, and control algorithms to address real-world challenges in autonomous systems and robotic perception. He has worked on a range of projects involving Visuomotor policies, reinforcement learning, training deep neural networks, driver fatigue detection, and human-robot interaction.

Amir is currently focused on building perception-driven robots capable of reasoning, adapting, and operating in complex environments. He enjoys working at the intersection of AI and robotics—where algorithms meet physical systems—and has experience deploying models in both simulated and real-world settings.

With a systems-thinking approach, Amir combines research depth with hands-on engineering to design scalable, efficient, and adaptive robotic solutions. He is passionate about continuous learning, collaboration, and advancing the frontier of intelligent autonomous behavior.