Regular biography
Daniele De Martini is an Associate Professor of Engineering Science at the University of Oxford, affiliated with the ME department. His research focuses on engineering science, though specific details are not provided. De Martini's work contributes to the academic and research community at Oxford. His profile page can be accessed at https://eng.ox.ac.uk/people/de-martini.
Scholar-generated biography
Daniele De Martini is a Departmental Lecturer in Mobile Robotics at the Oxford Robotics Institute, specializing in mobile robotics, deep learning, and cyber-physical systems. His research focuses on developing advanced algorithms for real-time perception, localization, and navigation in dynamic environments. De Martini's work includes online fall detection using recurrent neural networks on wearable devices, radar-based localization techniques, and semantic segmentation with FMCW radar. He also explores the integration of machine learning with satellite and LiDAR data for robust autonomous systems. His research emphasizes the co-design of sampling, communication, and prediction for synchronizing physical and digital models in the metaverse. De Martini's contributions span both supervised and self-supervised learning approaches for improving the reliability and performance of autonomous systems in challenging real-world scenarios.