My research is focused on methods and systems that assist users in complex, necessary analytical tasks for data intelligence. These tasks require advanced data management, integration, fusion, cleaning, and knowledge discovery that scale to very large datasets. The final goal is to let the users focus exclusively on the logic of their application, without being aware of the underlying models or of the execution details. My work draws from techniques in several areas, including data management, data mining, and machine learning, and solves problems in relational, semi-structured and cross-modal data (from various physical as well as social sensors, images, texts, microblogs, etc.). My focus is on the following key aspects of Data Science:
Partial lists can be found in: [DBLP] [ResearchGate] [GoogleScholar] [LinkedIn]
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As an Associate Professor (with tenure) from 2000 to 2010 and a Full Professor from 2017 to 2018, I taught (lessons and practical work) from 192 to 300 hours per year at the Computer Science departments of several universities and engineering schools: Aix-Marseille University (PolyTech'Marseille), University of Montpellier 2, University of Toulon, University of Avignon, and University of Rennes 1, INSA Rennes, ENST Brest in France as well as at University of Cape Coast in Ghana and University of Yaoundé in Cameroon, Africa in the volunteering initiative of AHED (Academics for Higher Education & Development)). I’ve developed numerous lecture notes, slides, and other pedagogical materials for undergraduate and graduate students on various topics of Data Science:
Laure Berti-Équille is a Research Director at Institut de Recherche pour le Développement (IRD), the French research institute for sustainable development, in ESPACE-DEV U228 research unit. Before, she was a full professor at Aix-Marseille University (AMU), senior scientist at Qatar Computing Research Institute (Hamad Bin Khalifa University, Qatar), Associate Professor (with tenure) at University of Rennes 1 (France), and visiting researcher at AT&T Labs Research (USA) as a recipient of the prestigious European Marie Curie Outgoing Fellowship. Her interests are at the intersection of large-scale data analytics, and statistical machine learning with a focus on anomaly detection with more than 80 publications and three monographs. She initiated the very first workshop editions on information and data quality in information systems (IQIS 2005) and in databases (QDB 2009 and 2016) in conjunction with SIGMOD and VLDB respectively, and co-organized the first French workshops on Data and Knowledge Quality in conjunction with EGC (Extraction et Gestion de Connaissances) in 2005, 2006, 2010, and 2011. She has received various grants from the French Agency for National Research (ANR), the French National Research Council (CNRS), and the European Union.
Laboratoire d'Informatique et Systèmes (LIS)
Domaine Universitaire de Saint-Jérôme
Avenue Escadrille Normandie-Niemen
13397 Marseille Cedex 20, France
Prof. Laure Berti-Équille, Ph.D.
laure DOT berti AT ird DOT fr
(+33) 04 91 05 60 16
Here are some quotes, pieces of advice, and thoughts I have been collecting through the years in the academia (anonymity preserved):