Barkin Dagda
AI & Robotics Researcher | PhD in Automotive Engineering
AI & Robotics Researcher | PhD in Automotive Engineering
2024 - PhD Foundership Award
2022-2026 - PhD in Automotive Engineering – University of Surrey, CAV Lab
2021-2022 - MSc in Electronic Engineering – University of Surrey, Distinction
2017-2021 - BEng (Hons) in Mechanical Engineering – University of Surrey, First Class Honours
A novel approach integrating LLM, RL, and PID-based control to create interpretable, safe, and efficient navigation strategies. [View Paper]
Investigating VLMs as semantic priors to guide RL policies in high-risk traffic scenarios, specifically for occluded pedestrian crossings. [View Paper]
Using vision-language models to enhance vehicle localization accuracy in challenging environments. [View Paper]
Critical evaluation of behavioral cloning approaches in autonomous driving scenarios. [View Paper]
Comprehensive review of core autonomous driving technologies. [View Paper]
Role: Research Scientist → Senior Research Scientist
I worked with LLMs and VLMs, applying techniques such as fine-tuning, RAG, function calling, and other advanced implementation methods. I developed autonomous software agents that integrated LLMs and VLMs for dynamic UI understanding and task execution.
I was promoted to Senior Research Scientist, leading the successful commercialization of SAM-Desktop, a proposal since adopted by Lenovo. My role included architectural planning, back-end development, and cross-functional leadership.
Role: Robotics Researcher
Worked on advanced control systems and digital twin simulations for autonomous mobile robots in warehouse and nuclear applications. Developed AI-driven load balancing and localization systems in GPS-denied environments.
Role: PhD Researcher
Investigating how vision-language models can guide reinforcement learning policies in safety-critical autonomous driving scenarios, particularly occluded pedestrian crossings and highway navigation.
