Ali Rabiee

Background

About Ali Rabiee

I am a PhD candidate in AI and Robotics at the University of Rhode Island, currently working on medical robotics and human-centered assistive technologies. With over 5 years of experience in machine learning, robotics, signal processing, computer vision, and reinforcement learning, I bring both academic expertise and practical experience to my research and development work. My research integrates techniques such as reinforcement learning, computer vision, and biosignal processing to design human-in-the-loop and shared autonomy systems. I specialize in creating vision-based systems for autonomous reach-to-grasp tasks and assistive robotic arms, applying reinforcement learning algorithms to improve robotic control. I also develop multimodal frameworks combining reinforcement learning with real-time user inputs, enabling intuitive control for individuals with severe impairments. In addition to my academic research, I have professional experience as a Machine Learning Engineer, where I developed and optimized computer vision algorithms for applications such as car damage detection, improving automation efficiency for insurance companies. My technical skills include extensive experience with ROS, MoveIt, PyBullet, Gazebo, and Kalman filters for state estimation and motion tracking. I am proficient in Python, C++, MATLAB, SQL, and deep learning frameworks like TensorFlow and PyTorch. I have worked with computer vision techniques, including YOLO for object detection, SLAM for 3D mapping, and multi-view geometry for pose estimation, along with applying advanced machine learning models such as deep reinforcement learning and imitation learning.