Romain Chor

Position: research engineer in Statistics INDICATE

Who am I and what do I do?

I am based in Paris, France. I hold a M.Sc. in Statistics and a Ph.D. in Statistical learning. 

I previously worked as a research engineer in Gustave Eiffel University. 

My background includes several areas of applied Mathematics such as Statistics, Statical learning, Optimization and Information Theory. 

What do I do in INDICATE?

I joined INDICATE as a research engineer in Statistics, to contribute to WP6 use case 2, in Lariboisière hospital (APHP, France). In particular, my work focuses on early detection of organ failure based on time series data. 

What motivates me to be part of INDICATE?

During my Master’s degree, I followed a lecture on applications of Machine Learning to healthcare. Since then, I have always wanted to use my skills in Statistics and Machine Learning to help improve research in medical fields.

INDICATE is a great opportunity to work on various fascinating tasks, using data from diverse sources.

How does my background or expertise contribute to the goals of INDICATE?

My previous work was focused on Federated Learning, a branch of Machine Learning dedicated to collaborative training of models using spatially distant machines and data sources. Federated Learning is particularly adapted for e.g., guaranteeing privacy and optimizing computational resources, therefore naturally helps tackling constraints inherent to medical data and models.

I expect to find cases in which Federated Learning will be useful for INDICATE’s objectives.