Laia Garrobé Fonollosa

As an undergraduate student of a double degree in Mathematics and Physics at Universitat the Barcelona (UB), I found my way to marine ecology during a 10-month internship at the Oceanography Department of UCLA. I then went on to work as a data science engineer for high-performance environments before deciding to move to St Andrews to pursue an MSc in Marine Mammal Science in 2020, where I started my PhD two years after in collaboration with the Electrical Engineering Department at the University of Strathclyde. Because of my background, my interests lay in the intersection of computer science and bioacoustics. In my free time, I can be found knitting, hiking, or playing board games.

Harnessing the power of machine learning algorithms for the detection of marine mammal species in large acoustic datasets

PhD aim:

This project will focus on developing a framework for efficient detection of cetaceans from long-term acoustic datasets by designing machine learning algorithms to characterize the underwater soundscape and to detect and classify marine mammal vocalisations.

PhD objectives:

While the objectives are yet TBD, during the first years we will focus on studying the transferability of existing ML and traditional detection algorithms and designing a pipeline to improve generalisation to new unseen datasets.

Contact details:

Email: [email protected]
Twitter: @_garrobe