Domenico Cappello Email and Phone Number

Unmanned systems and AI- Multi-agent planning, robotic coordination, perception

- Solved autonomous collision-free navigation problems of multi-vehicle systems with limited communication capabilities using differential game-theoretic techniques- Published and reviewed papers for top-tier journals and conferences in the field of systems and control- Designed and performed robotics experiments in the Imperial Aerial Robotics Laboratory- Supervised final projects of undergraduate students and project of the International Research Opportunities Programme (IROP) 2019- Assisted in teaching first and second year laboratories of "Computing" and "Numerical Analysis" courses of Aeronautics and the Change Makers course "Global challenges: innovating for change"

- Investigated supervised and unsupervised learning techniques for enhancing prediction capabilities of continuous glucose monitoring systems- Developed a novel neural network-based multi-model observer for time series forecasting

- Developed data-driven algorithms for improved estimation and prediction performances of commercial continuous glucose monitoring systems for Diabetes

- Tackled image classification and object detection problems arising in vision-based control of cooperative fleet of heterogeneous mini and micro UAVs via Deep Learning techniques- Developed efficient genetic algorithm-based solutions for displacement of a limited number of cameras for surveillance systems with optimal coverage in known environments