Maria Brbic

EPFL IC IINFCOM MLBIO
INJ 330 (Bâtiment INJ)
Station 14
1015 Lausanne

Expertise

Machine learning, computational biology
Maria Brbic (https://brbiclab.epfl.ch/) is an Assistant Professor of Computer Science and Life Sciences at EPFL. She is also affiliated with the EPFL AI Center and EPFL Institute of Bioengineering (IBI). Prior to joining EPFL, Maria was a postdoctoral researcher in Computer Science at Stanford University working with Jure Leskovec and was a member of
the Chan Zuckerberg Biohub at Stanford.
She received her PhD degree from University of Zagreb in 2019, while also researching at Stanford University and University of Tokyo. Her research was awarded with the Fulbright Scholarship, L'Oreal UNESCO for Women in Science Scholarship, Branimir Jernej award for outstanding publication in biology and biomedicine, and Josip Loncar Silver Plaque award for the best doctoral dissertation. She has been named a Rising Star in EECS by MIT in 2021 and she received an Early Career Award by SIB in 2023. Her research is focused on developing new machine learning methods and applying her methods to advance biomedical research. Her contributions to the field have earned her prestigious funding, including the SNSF Starting Grant. Maria is a CIFAR Fellow in the Multiscale Human Program.

Teaching & PhD

PhD Students

Yulun Jiang, Siba Smarak Panigrahi, Shuo Wen, Tingyang Yu, Shiqiu Yu

Past EPFL PhD Students

Artem Gadetskii (2026)

Courses

Deep learning in biomedicine

CS-502

Deep learning offers potential to transform biomedical research. In this course, we will cover recent deep learning methods and learn how to apply these methods to problems in biomedical domain.

Transfer learning and meta-learning

CS-625

This seminar course covers principles and recent advancements in machine learning methods that have the ability to solve multiple tasks and generalize to new domains in which training and test distributions are different.