Daniele Gammelli is a postdoctoral scholar in Stanford’s Autonomous Systems Lab, where he focuses on developing learning-based solutions that enable the deployment of future autonomous systems in complex environments, with an emphasis on large-scale robotic networks, mobility systems and autonomous spacecraft. He received his Ph.D. in Machine Learning and Mathematical Optimization at the Technical University of Denmark, where he developed ML-based solutions to analyze and control future Intelligent Transportation Systems.
More broadly, his research interests include deep reinforcement learning, generative models, graph neural networks, bayesian statistics, and control techniques leveraging these tools.
Beyond research, Daniele enjoys practicing soccer, going on trail runs, reading, and cooking.
- Kaj and Hermilla Ostenfeld’s Excellence Research Fund