Bruno F. Santos

Bruno F. Santos is an Assistant Professor in Airline Operations at Delft University of Technology's Faculty of Aerospace Engineering. His research bridges theoretical optimization methods with practical airline operations challenges, focusing on making aviation systems more efficient and sustainable through data-driven approaches.

Dr. Santos's research interests center around aircraft maintenance optimization, predictive maintenance using AI, stochastic modeling for airline operations, and strategic planning for sustainable aviation. His work applies advanced computational techniques including Bayesian frameworks and deep reinforcement learning to solve real-world problems in the aviation industry. A key focus is transforming traditional fixed-schedule maintenance into condition-based approaches that respond to actual aircraft system health.

His recent publications demonstrate a strong trajectory in high-impact journals, with a focus on counterfactual explanations for remaining useful life estimation, deep reinforcement learning for airport operations, and multidisciplinary coupling for hybrid-electric aircraft design. These works collectively address the critical challenge of making aviation more efficient, sustainable, and cost-effective through digital transformation.

• TRA VISIONS 2022 Senior Researcher Award Airborne
• AIAA Electrified Aircraft Technology Technical Committee Best Paper Award (2023)
• AIAA Software Best Paper Award (2024)

Dr. Santos leads significant research initiatives including the €6.8 million ReMAP project, which successfully demonstrated through a six-month trial at KLM that AI models can predict aircraft system health and optimize maintenance scheduling. This project involved collaboration with multiple European universities and industry partners. His editorial roles for Transportation Research Procedia and Transport Policy demonstrate his standing in the academic community. Dr. Santos actively translates research into practical applications, with media coverage highlighting how his work can save airlines hundreds of millions while improving operational efficiency.

His Aircraft Maintenance and Operations Research Group focuses on developing adaptive maintenance planning systems that use real-time data to optimize maintenance scheduling, reducing unnecessary maintenance while preventing system failures. The group's work represents a significant shift from traditional fixed-schedule maintenance to condition-based approaches that respond to actual aircraft system health.