I am a microbiologist interested in plankton species due to their role in regulating Earth Climate and supporting aquatic food webs. Over the years, I’ve learned to work on plankton taxonomy (species identification), imaging instruments (plankton images can help us count and identify species or possible interactions like predation), and mathematical models, including machine learning models for automatic image recognition. My main research objective consists in understanding the drivers of plankton diversity and dynamics in aquatic ecosystems, as both are important indicators of ecosystems functioning and services.

My research project at the University of Geneva aims at understanding the environmental conditions leading to blooms of microscopic algae and cyanobacteria (phytoplankton) in Lake Geneva: Efflorescences Algales dans le Léman face aux changements GlobAux (project ALGA). Lake Geneva provides essential services for local communities, serving as a source of drinking water, recreational and touristic activities, and supporting local fisheries. Early on, these services have been threatened by massive proliferations of phytoplankton, which discolored the lake, clogged fishermen nets or produced nauseous gas. Despite longstanding efforts to reduce these proliferations, Lake Geneva still suffers from sudden outbreak of diverse phytoplankton groups, including potentially toxic species. To understand what conditions (meteorological, hydrological, and/or biological) favor the blooms, we will be monitoring phytoplankton communities in the vicinity of the Lac Léman exploration platform (LéXPLORE) using various imaging instruments. Ultimately, our team aims at developing an AI-based image classification tool to assess the near-real time dynamics of phytoplankton groups, provide early blooms detection, and support the development of decision tools for lake stakeholders.