Survival analysis and machine learning

Alonso Silva

Currently working at Safran as Senior Machine Learning researcher

2012/2018 : Bell Labs

2011/2012 : postdoctoral researcher in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley

2010/2011 : postdoctoral researcher in the Department of INRIA Paris Rocquencourt

2010 : Ph.D. in Physics from the École Supérieure d'Électricité Ph.D. at INRIA Sophia-Antipolis, France

2006 : B.Sc. of Mathematical Engineering and Mathematical Engineering degree from the Department of Mathematical Engineering (DIM) at the Universidad de Chile

Every week, our students assist to a lecture which is in link with the current world and the Bachelor programme.

This enlightment session explained to students what survival analysis is.

It was historically developed and used by actuaries in insurance and in medical researches to measure lifetime of population and expected lifetime of patients.

Alonso applied this concept to several modern examples of survival analyses using the Kaplan Meiser estimation like the duration of a dictatorship versus a democracy or analysing the customer churn data using a logistic regression.

"Survival analysis is useful when your data has a bith, a death and a right censorship". Alonso uses this concept to estimate the life expectation of planes and helicopters of the Safran fleets.

"Machine Learning can help us to better understand datas".