Benjamin Renoust

Director of Data and Knowledge Engineering @Median Technologies

Antibes, FR
MOBILE NUMBERS
+91 *********19

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WORK HISTORY

Oct 2019 — Present

Director of Data and Knowledge Engineering @Median Technologies

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Valbonne, FR

Director of Data and Knowledge Engineering, eyonis Senior Data Scientist Artificial Intelligence and Data ScienceRefine the data to power our AI factory. The data and knowledge engineering team handles the data lifecycle from ingestion to ML preparation. Includes visual analytics and knowledge representation and mining.We organize data, manage all ETL pipelines to prepare data and collect, curate, and align ground truth before experiments. We run experiments to evaluate different facets of our AI products. We are in charge of the design and execution of all the independent verification, and FDA validation of our AI products.

EDUCATION

2009 — 2013

Université de Bordeaux

Doctor of Philosophy (Ph.D.), Computer Science

2007 — 2009

Korea Advanced Institute of Science and Technology

Engineer - Master, Computer Science

2005 — 2008

UTBM

Engineer - Master, Image, Interactions and Virtual Reality

2003 — 2005

Université Marie et Louis Pasteur

DUT, Computer Science

SKILLS

Information VisualizationResearchAlgorithmsData MiningData VisualizationComputer ScienceComplex NetworksProgrammingGraphs

ABOUT BENJAMIN RENOUST

Understanding the world in its complexity is a fascination which questions the place of human beings in the whole system. We do so by capturing the reminiscences of our interactions with the world and yet we merely grasp its comprehension. Often in our attempts to observe the world, we look at these precise interactions, at the level of which, networks appear to be an excellent means of study. We can visualize them, manipulate them, and analyse them. They are abstract structures and yet easy to visually interpret, almost as if they were tangible objects. Graph theory provides us strong means of analysis of networks, and their visualization challenges us in exploring them.I am fascinated by the explanatory power of such models, and my research aims at using the most adequate tools from theory to visualization to empower understanding of complex phenomena. I intend to confront my work with as many application domains possible, each enriching our research with a new set of questions and challenges pushing further our work.

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