As a senior scientist at QCRI, Laure’s research focus is on data quality, truth discovery, anomaly detection, data cleaning, data integration and statistical machine learning.
Laure Berti-Équille received a M.Sc. degree in Physics from the University of Toulon (France) in 1995 and a M.Sc. degree in Computer Science from the University of Paris Dauphine (France) in 1996. She earned a Ph.D. degree in Computer Science from the University of Toulon (France) in 1999. In 1999-2000, she was an Assistant Professor at the University of Avignon (France). In 2000-2010, she was a tenured Associate Professor at the University of Rennes 1 (France) and received her "Habilitation" in June 2007. From September 2007 to December 2009, she was a visiting researcher at AT&T Labs Research, New Jersey (USA) involved in several projects related to data quality management and data mining. In January 2011, she joined IRD (Institut de Recherche pour le Développement), the French Institute of Research for Development as a “Directeur de Recherche” in Computer Science.
Since 2000, she has published two monographs, several book chapters, and over 70 research papers in refereed journals and conferences, she has served in organizing committees and the program committees of more than 50 international conferences and workshops. She is an associate editor of the ACM Journal of Data and Information Quality (JDIQ).
Laure's research has been supported by the French National Agency for Research (ANR) and by the European Commission. She was the recipient of a 3-year fellowship funded by the European Commission - FP7 Mobility Marie Curie OIF in 2007-2010 (selection rate: 18.8% of 445 submissions, Grant FP6-MOIF-CT-2006-041000).
Book - Chapters
• Laure Berti-Equille, Javier Borge-Holthoefer, Veracity of Data: From Truth Discovery Computation Algorithms to Models of Misinformation Dynamics. Synthesis Lectures on Data Management, Morgan & Claypool Publishers, December 2015.
• L. Berti-Équille, La qualité et la gouvernance des données au service de la performance des entreprises (Book in French), Traité IC2, Hermès, ISBN 978-2-7462-2510-7, ISS 2111-0360.
• L. Berti-Équille, I. Comyn-Wattiau, M. Scannapieco (Eds). Proceedings of the 17th International Conference on Information Quality (ICIQ 2012), Paris, 16-17 November 2012.
• X. L. Dong, L. Berti-Équille, D. Srivastava: Data Fusion : Resolving Conflicts from Multiple Sources. In: S. Sadiq (ed.), Handbook of Data Quality - Research and Practice, Springer-Verlag Berlin Heidelberg 2013.
• F. Moussouni, L. Berti-Équille, Cleaning, Integrating, and Warehousing Genomic Data from Biomedical Resources, Chapter 2 of "Biological Knowledge Discovery Handbook: Preprocessing, Mining and Postprocessing of Biological Data", M. Elloumi, A. Y. Zomaya (Eds), Wiley Book Series on Bioinformatics: Computational Techniques and Engineering, Wiley-Blackwell, John Wiley & Sons Ltd., New Jersey, USA (Publish.) ISBN: 978-1-118-13273-9, September 2013.
Journal and Conference papers
• Andrés Troya-Galvis, Pierre Gançarski, Laure Berti-Equille. A collaborative framework for joint segmentation and classification of remote sensing images. Advances in Knowledge Discovery and Management, Springer 2016.
• Laure Berti-Equille, Ji Meng Loh, Tamraparni Dasu. A masking index for quantifying hidden glitches, Knowledge and Information Systems, Springer, July 2014, Online ISSN 0219-3116.
• Mohamed Yakout, Laure Berti-Equille and Ahmed Elmagarmid. Don't be SCAREd: Use SCalable Automatic REpairing with Maximal Likelihood and Bounded Changes. Proceedings of the 2013 ACM SIGMOD/PODS Conference, New York, June 2013
• Laure Berti-Equille, Tamraparni Dasu, Divesh Srivastava. Discovery of complex glitch patterns: A novel approach to Quantitative Data Cleaning. Proceedings of International Conference on Data Engineering (ICDE 2011), pp. 733-744, Hannover, Germany, April 2011.
• Minji Wu, Laure Berti-Equille, Amélie Marian, Cecilia M. Procopiuc, Divesh Srivastava. Processing Top-k Join Queries. Proceedings of VLDB, Singapore, September 2010.
• Xin Luna Dong, Laure Berti-Equille, Divesh Srivastava. Integrating conflicting data: the role of source dependence. Proceedings of the International Conference on Very Large Databases (VLDB 2009), Lyon, France, August 2009.
• Xin Luna Dong, Laure Berti-Equille, Divesh Srivastava. Truth discovery and copying detection in a dynamic world. Proceedings of the International Conference on Very Large Databases (VLDB 2009), Lyon, France, August 2009.
• Laure Berti-Equille. Quality-Aware Association Rule Mining. Proceedings of the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006), LNCS 3918, pp. 440-449, Singapore, April 9-12, 2006.
• Detecting dependence between sources, United States Patent 8190546, issued 5/29/2012 and co-invented with X. L. Dong and D. Srivastava
• Scalable Automatic Repair for minimal change and maximal likelihood, European Patent 12724324.4 issued 5/25/2012 and United States Patent filed on May 2011, co-invented with Mohamed Yakout and Ahmed K. Elmagarmid
PROFESSIONAL ACTIVITIES AND SERVICES
Associate and Guest Editor
• Associate Editor of the international journal ACM Journal on Data and Information Quality;
• Guest editor of a Special Issue in IEEE Transactions on Big Data on Data Quality (to appear in 2017)
• Editor of 7 proceedings of national and international workshops and conferences (ICIQ 2012, QDB 2009 in conjunction with VLDB 2009, IQIS 2005 in conjunction with ACM SIGMOD 2005, QDC 2005, 2006, 2010, and 2011 in conjunction with the French conference EGC);
• Journal referee: Journal of Data Management Research.
• Editorial board member of Journal on Information Quality and Journal of Digital Information Management.
Program and Organization Chair
• Co-chair of ICIQ 2016, the 21st International Conference on Information Quality, Ciudad Real, Spain;
• Co-organizer of the International Quality in Databases workshop (QDB 2016) selected in conjunction with VLDB 2016, Delhi, India, September 2016;
• Principal PC chair of ICIQ 2012, the 17th International Conference on Information Quality, Paris, France.
• Co-organizer and PC-co-chair of two international workshops Information Quality in Information Systems (IQIS 2005) and Quality in Databases (QDB 2009) in conjunction ACM SIGMOD 2005 and VLDB 2009 respectively;
• Co-organizer and PC chair of four workshop editions on Data and Knowledge Quality (QDC 2005, 2006, 2010, and 2011) in conjunction with the French conference on Data mining;
• Co-founder of EXQI, the first non-profit organization dedicated to data quality and data governance networking for French companies;
• PC member of more than 50 international and national conferences and workshops since 2010.
• PhD Jury Committee Member and PhD Reviewer of 10+ PhD candidates
• Supervision of 40+ young researcher internship
From 1996 to 2007, as a tenured Associate Professor, Laure taught (lessons and practical work) from 192 to 300 hours per year at the Computer Science departments of several universities and engineering schools: University of Montpellier 2, University of Toulon, Aix-Marseille University, 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) http://www.awb-usf.org/. She has developed numerous lecture notes, slides, and other pedagogical materials for undergraduate and graduate students on the following topics:
- Data Mining and Machine Learning
- Database Management Systems, Advanced Database Administration and Tuning
- Data Warehousing
- Semantic Web Technologies
- Software Engineering Project Management
In the Media
Researchers from MIT and the Qatar Computing Research Institute have developed a novel new facility in the current rush of interest towards computer vision – an algorithm that can identify overweight...
A growing number of people have expressed their concern about high levels of polarization in society. For instance, the World Economic Forum's report on global risks lists the increasing societal ...
Big data is a big deal. With these huge data sets, analysts can gain unprecedented insight into the hidden patterns of fields like physics, healthcare, and finance. Collecting and analyzing this data...
The QCRI – MIT CSAIL Annual Research Project Review is open to the public on Monday, March 27, 2017, at the HBKU Research Complex Multipurpose Room. The annual meeting is a highlight of a ...
Machine Learning and Data Analytics Symposium - MLDAS 2017 Building on the success of the three previous events , Boeing and QCRI will hold the Fourth Machine Learning and Data Analytics Symposium (...
The Boeing Company has announced that it will once again partner with the Qatar Computing Research Institute (QCRI), part of Hamad bin Khalifa University, to host the fourth annual Machine Learning ...