Héctor Climente-González

As a Lead Data Scientist in Novo Nordisk, my goal is to find genetic predictors of disease that are useful for diagnosis, treatment, and understanding the underlying biology. To that end, I use machine learning to assist with modeling, biomarker discovery and variant interpretation.

I have over 10 years of experience in computational biology and applied statistics. I completed my PhD in MINES ParisTech, under the supervision of Chloé-Agathe Azencott. In my thesis I explored graph-based methods for genetic studies. Afterwards, I was accepted into RIKEN’s SPDR program to conduct my postdoctoral research with Makoto Yamada. I focused on the development and application of novel machine learning methods for feature selection.