Barkin Dagda

Contributed to Innovate UK projects focusing on autonomous robots for warehouse operations. Designed a digital twin simulation for an AMR, integrating advanced sensors and developing control algorithms using ROS to optimize performance and safety.

Led the development of autonomous software agents using LLMs and VLMs, focusing on task automation and dynamic UI understanding. Successfully commercialized two products, including SAM-Desktop, adopted by Lenovo. Responsibilities included architectural planning and collaboration with cross-functional teams.

Developed advanced robotic systems, including prototype platooning vehicles and telepresence robots. Created algorithms for leader-follower behavior and wireless control, utilizing computer vision techniques for autonomous navigation.

My PhD research focused on vision-based localization for autonomous vehicles, with an emphasis on developing approaches that leverage multi-modal data sources and foundation models such as DINOv2, SAM, and CLIP. I gained expertise in computer vision, image processing, and self-supervised learning, working extensively with transformer-based architectures and vision transformers (ViTs) to enhance im

Grade: Distinction

Modules included Computer Vision and Pattern Recognition, Speech and Audio Processing and Recognition, Image Processing and Deep Learning, AI and AI Programming, Robotics, Fundamentals of Mobile Communications, Applied Mathematics for Communication Systems, Advanced Mobile Communication Systems.

Grade: First Class Honors

Modules included Mathematics, Fluid Mechanics and Thermodynamics, Design and Component Production, Electronic Instrumentation, Mechanics of Vehicles and Machines, Engineering Management, Control and Dynamics, Numerical Methods.