About Me

Hello! I’m Amir Etefaghi Daryani, a passionate computer vision researcher dedicated to developing intelligent systems that help machines perceive and interact with the world. My work centers on vision-based perception and decision-making—critical tasks for enabling autonomous robots to navigate complex human environments. I focus on innovative solutions in object and person detection, multiple object tracking, social trajectory forecasting, and human pose prediction. Currently, as a Graduate Research Assistant at the University of Florida, I’m actively involved in pioneering projects such as CLASP, a real-time system that correlates passengers with their belongings to enhance airport security; CaMuViD, which addresses the challenges of multi-view object detection in crowded scenarios; and ViLAD, where I contribute to advancing agricultural robotics through video-based lettuce association and detection. My earlier research experience at Mizanir Research Institute in Tehran allowed me to explore compelling challenges in image inpainting and forensic detection with projects like E2F-GAN and IRL-Net. I am pursuing a PhD in Agricultural and Biological Engineering at the University of Florida, complementing my Master’s degree in Electrical Engineering from Amir Kabir University of Technology and my Bachelor’s degree from the University of Guilane. With a strong foundation in programming languages such as Python, C++, Matlab, and frameworks like PyTorch and TensorFlow, I strive to push the boundaries of what’s possible in computer vision. My journey has been recognized through several prestigious fellowships and publications in top-tier venues, reflecting my commitment to excellence and innovation. I’m excited to continue exploring new frontiers in research and to contribute technologies that bring us closer to seamless human–machine interaction.