Filipe Rodrigues
Papers
1
Total Citations
6
H-Index
1
About
Filipe Rodrigues is a leading researcher at the intersection of artificial intelligence, transportation engineering, and urban computing. His work focuses on developing novel machine learning and reinforcement learning frameworks to optimize complex, real-world mobility systems. Rodrigues is best known for pioneering the application of Graph Neural Networks (GNNs) to autonomous mobility-on-demand (AMoD) systems, as demonstrated in his highly influential 2021 paper (6 citations). This work introduced a groundbreaking framework that uses GNNs to represent entire transportation networks as graphs, enabling reinforcement learning agents to coordinate fleets of self-driving vehicles with unprecedented efficiency. By modeling the intricate relationships between vehicles, passengers, and road networks, his approach significantly improves fleet management, reduces wait times, and enhances system scalability. His research has been instrumental in bridging the gap between theoretical AI and practical urban logistics, earning him recognition as a key figure in smart city innovation. With a growing citation impact, Rodrigues continues to shape the future of autonomous transportation, making cities more accessible and sustainable through intelligent, data-driven solutions.
Research Focus
Key Achievements
Top Papers
- 1