Data Science in Biodiversity

I’m the leader of the Biodiversity Data Science research group. Our research employs cutting-edge Data Science tools, such as machine learning, artificial intelligence, and big-data computational frameworks, to unravel the underlying mechanisms driving biodiversity. We work to understand and forecast global distribution patterns, ranging from genes to entire ecosystems, and from past climate fluctuations to future climate change scenarios. Our analyses consider anthropogenic impacts, such as climate change, habitat degradation, overexploitation, and the introduction of invasive species. We share our data under the FAIR principle (easy to find, access and reuse) to citizens, managers, and policymakers so that they can make informed decisions on the best strategies for protecting, conserving, and managing biodiversity.