Manuel B.

As a senior software engineer and computer science researcher, I combine valuable industry experience in MedTech and Banking with academic research in robotics, AI, medical augmented reality, and deep learning-assisted computer vision. After completing my MSc in Computer Science in Germany, where I specialized in Robotics and AI, I worked as a software engineer at Tecan, Credit Suisse, and Roche Diagnostics. These roles allowed me to tackle complex front- and back-end software challenges. At Roche Diagnostics, I served as an algorithm expert, implementing mathematical-numerical optimization methods and machine learning-based features for PCR test evaluation. In academia, I have contributed to research at the Cognitive Robotics Lab at ENSTA ParisTech in France, where I implemented complex human-robot interaction scenarios in the field of socially assistive robotics. In a short project at the Sensory-Motor Systems Lab of the Institute of Robotics and Intelligent Systems at ETH, I worked on deep learning-supported computer vision tasks, with a focus on video-based human pose estimation in climbing. Currently, I am completing my PhD at University College London (UCL), focusing on medical augmented reality and deep-learning-assisted computer vision (thesis submission planned in January 2025). My research explores deep-learning-based egocentric hand and tool pose estimation. I also have a passion for teaching and mentoring. At UCL, I work as a teaching assistant, helping university students understand machine learning and software engineering concepts. Since October 2023, I have been a teaching assistant for the prestigious GATSBY Unit for Computational Neuroscience at UCL. I support highly selective machine learning courses, including “Probabilistic and Unsupervised Learning” and “Approximate Inference and Learning in Probabilistic Models.” My work bridges practical industry applications and cutting-edge academic