Esther Pacitti - Home Page

  
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 Professor in Computer Science in University of Montpellier 2, Lirmm & Inria

Short Bio

Short Bio

I'am professor of computer science at University of Montpellier 2 since 2009, pursuing research in distributed and scientific data management in different contexts. Previously, she was an assistant  professor at University of Nantes  (2002-2009) and a member of Atlas INRIA team.  I obtained my  “Habilitation à Diriger les Recherches” (HDR) degree in 2008 on the topic of  data replication on different  contexts (data warehouses, clusters and peer-to-peer systems). Since 2004 I'am serving  as program committee member of major international conferences (VLDB, SIGMOD, CIKM, etc) and has edited and  co-authored several books. She has also published a significant amount of  technical papers  and journal papers in well known international conferences and journals.

HDR (University of  Nantes) 2008, Ph.D (PUC-Rio and Inria) 1998

Contact

Laboratoire d'Informatique, Robotique et Micro-Eletronique de Montpellier (Lirmm)

Campus St Priest - BAT 5, Office 02/243
860 rue de St Priest
34095 Montpellier cedex 5 

Tel: 04 67 14 97 27

Esther.Pacitti@lirmm.fr

Research Interests

I'am co-head of the EPI Zenith and my research interests are related to distributed data management in different contexts  as explained below.

My research activities are focused on distributed data management (data replication, query processing, etc). Since 2009 I have been investigating new  search and  recommendation techniques for distributed data management. More precisely, I investigate  new recommendation methods and distributed algorithms to deploy search and recommendation  over different types  distributed architectures. The results of this research may be applied to  to web  and scientific data. For instance, in Pl@ntNet project, recommendation methods based on diversity are very useful for plant identification. This research activity is supported by CNRS Mastodons Project and Numev PIA.

I'am  also involved in data-intensive scientific workflows over geographically distributed clouds. The problem here is to fragment a data intensive scientific workflow taking into account data transfer and load balance. This joint project between the Kerdata and Zenith teams is funded by Microsoft in the context of the Joint Inria – Microsoft Research Centre. The project addresses the problem of advanced data storage and processing for supporting scientific workflows in the cloud. The goal is to design and implement a framework for the efficient processing of scientific workflows in clouds. Our approach will leverage the cloud infrastructure capabilities for handling and processing large data volumes.

Publications

Please visit  my DBPL PAGE. If you want any particular paper please contact me

Teaching Activities

I'am actually professor at Polytech Montpellier2 in the Department of Computer science and Management.

I'am responsable for the following courses:

       -Databases (Relational Algebra, SQL, E-R Model, Transaction Management, Query Processing and Optimization, etc)

       -Distributed Databases (Conception, Fragmentation, Distributed query and transaction processing,  Parallelism, MongoDB, etc) 

       -Big Data Management (Data Management in the Cloud, Map Reduce, Recommandation, Gragh Databases) , etc

I also teach in the master  of computer science, and I'am responsible of the cours:

      - Large Scale Data Management

Besides my teaching activities, I also supervise

        - Engineers students in industrials projects and training

         -Master and Phd Students 

Projects

Since 2009, the most relevant projects I've been involved are the following:

CNRS Mastodons:  (2011 - today)

EDF: Privacy Preserving Data Mining in P2P Networks (2013 -2014)

BigDataNet:  (2013 - 2015)

Music, Inria-Faperj: (2014 - 2016) 

ANR Verso DataRing: (2009-2011)

Tags

Distributed Data Management, Data Replication, Query Processing, Recommendation, Distributed Scientific Workflow Management

Last update on 28/09/2015