Brice CHARDIN
  • Associate Professor
  • Data Engineering
  • ISAE-ENSMA

Lecture Activity

1st year:

  • Algorithms and numerical systems
  • Fundamentals for software design
  • Signals and systems
  • Introduction to Data Science

2nd year:

  • Project in avionics (drone simulation with ardupilot)
  • Applied Machine Learning

3rd year:

  • Advanced design project
  • Smart data (data mining and machine learning)

Research Activity

I am an associate professor at ISAE-ENSMA and a member of the LIAS Data and Model Engineering team since 2013.

Energy data management and forecasting

My PhD thesis focused on distributed data management solutions on flash memories to handle sensor data produced by power plants at EDF, an energy company. In this project, we developed a specialized NoSQL system, named Chronos, distributed under an open-source license, along with a benchmark designed to evaluate DBMSs in the context of industrial process data management.

I collaborated with two local industrial partners: SRD (an electricity distribution operator) and Nexeya (an energy storage solutions manufacturer) to perform predictive analysis of energy consumption and production.

Clustering under dissimilarity constraints

I am involved in the development and evaluation of clustering under intra-cluster dissimilarity constraints algorithms. The goal of such algorithm is to identify clusters while providing strong error bounds when electing a representative element.

Pattern mining

In 2012-2013, I held a postdoctoral research position at LIRIS on pattern mining within the ANR DAG project, in which we designed a Rule Query Language. RQL is a SQL-like pattern mining language that extends and generalizes functional dependencies to new and unexpected rules.

Query relaxation

Since 2016, I have been working on query relaxation on top of RDF knowledge bases to answer why-empty, why-so-many and why-so-few questions on SPARQL queries.