Guadalupe Gonzalez

Guadalupe Gonzalez

Guadalupe is a fourth-year PhD candidate at Imperial College London in the Department of Computing. She received her B.Sc. in Biomedical Engineering and M.Res. in Data Science before adventuring into the exciting field of deep learning on graphs advised by Michael Bronstein and Kirill Veselkov.During the first part of her PhD she enjoyed developing graph machine learning methods leveraging genomic data to uncover molecules with disease-beating properties in foods within the HyperFoods project. Motivated by the drawbacks of modeling genetic perturbations using machine learning approaches alone, she currently works on developing causal graph machine learning algorithms to model genetic and chemical perturbations together with Marinka Zitnik at Harvard Medical School.

Panelist

Imperial College London