Laure Berti-Equille is a Research Director (DR1) at IRD (Institut de Recherche pour le Développement), the French national research institute for sustainable development. She is based at the ESPACE-DEV joint research unit in Montpellier, France. Her research sits at the intersection of data management and machine learning, with a long-standing focus on data quality — how to measure it, clean and prepare data, discover the truth from conflicting sources, and build machine-learning systems that remain trustworthy when the data is imperfect.
Her current work covers data preparation and cleaning, truth discovery and fact-checking, trustworthy and uncertainty-aware machine learning, anomaly detection in time series, and multimodal deep learning. A cross-cutting theme is applying these methods to the United Nations Sustainable Development Goals — Earth-observation image analysis, biodiversity monitoring, and poverty estimation. She authored the open-access book AI for SDGs (EDP Sciences, 2025) and created open-source tools including Learn2Clean, a reinforcement-learning approach to sequencing data-preparation tasks.
She has published more than 200 papers in leading venues such as VLDB, SIGMOD, ICDE, KDD, ICLR, AISTATS and SIGIR. Before her current position she was a visiting researcher at MIT (LIDS), a senior research scientist at the Qatar Computing Research Institute, a full professor at Aix-Marseille University, a researcher at AT&T Labs–Research, and an associate professor at the University of Rennes. She earned her Habilitation (HDR) from the University of Rennes and her Ph.D. from the University of Toulon. She is a Senior Member of both IEEE and ACM and a member of the ELLIS society.