Motivation Valentin Bordoux

I am honoured to apply for the KIVI EngD Award. On August 28th, 2025, I became the first EngD graduate from Wageningen University to receive the distinction cum laude. My EngD focused on advancing sustainable marine biodiversity monitoring through an AI-driven passive acoustic monitoring system, that records and analyses underwater animal sounds. My thesis, “Revealing the Sounds of the North Sea: An Integrated Passive Acoustic Monitoring System for Improved Underwater Biodiversity Sensing,” exemplifies the multidisciplinary innovation that arises when engineering and computer science meet marine ecology.

Innovation 

The project pioneered an integrated Passive Acoustic Monitoring (PAM) system that combines AIbased sound detection, real-time embedded processing on a custom underwater recorder, and a user-friendly dashboard for biodiversity observation. To address one of marine bioacoustics’ key challenges, the lack of efficient data analysis methods and annotated data, I implemented a humanin-the-loop learning approach, combining active and transfer learning techniques. This made underwater sound recognition for fish and invertebrates more scalable, efficient, and reproducible, marking a major step toward automation in marine bioacoustics.

Impact 

Traditional methods for marine monitoring, such as trawling or diving surveys, are costly, invasive, and spatially limited. As seascapes continue to change rapidly due to climate change, fishing, and offshore energy development, there is an urgent need for scalable, non-invasive monitoring solutions. My EngD addresses this need by developing approaches for long-term, autonomous, and cost-effective acoustic monitoring. The integration of AI detection with real-time broadcasting enables continuous observation in harsh environments like the North Sea, providing essential data for ecosystem management and conservation. The project’s outcomes are already contributing to real-world applications: the developed system is being integrated into a European initiative for monitoring offshore wind farms, combining acoustic and visual sensors. All datasets and tools are openly shared1 to promote reproducibility and accelerate progress within the global research community. Combining audio and video sensing, the system also helps reveal the hidden wildlife of the North Sea, raising public awareness of underwater biodiversity.

Leadership & Collaboration 

This project thrived through intensive collaboration across disciplines: marine biology, software engineering, and data science. Coming from a robotics background, I faced a steep learning curve in machine learning and marine ecology. I actively sought guidance from experts within and beyond Wageningen University, growing from learner to contributor. I supported the development of a complex system, working closely with marine biologists and designers to align technical possibilities with ecological needs. These experiences strengthened my ability to communicate across disciplines and translate complex technical work into academic contributions and practical tools advancing research and management.

My EngD journey demonstrates how engineering innovation can serve sustainable development by bridging technology and ecology. I aspire to continue developing tools that enable society to understand and protect our oceans. Receiving the KIVI EngD Award would be a great honour and an opportunity to inspire the next generation of EngD candidates to combine scientific rigour with realworld impact for a more sustainable future