Maria Brbic
Web site: Web site: https://bioengineering.epfl.ch/
Web site: Web site: https://sin.epfl.ch
Web site: Web site: https://ssc.epfl.ch
Fields of expertise
Machine learning, computational biology
Biography
Maria Brbic (https://brbiclab.epfl.ch/) is is an Assistant Professor of Computer Science and, by courtesy, of Life Sciences at EPFL. She is also affiliated with the 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 received 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.Teaching & PhD
Teaching
Computer Science
Communication Systems
PhD Programs
- Doctoral program in computer and communication sciences
- Doctoral program in computational and quantitative biology
CS-625: Transfer learning and meta-learning
CS-502 Deep learning in biomedicine
Courses
Applied data analysis
This course teaches the basic techniques, methodologies, and practical skills required to draw meaningful insights from a variety of data, with the help of the most acclaimed software tools in the data science world (pandas, scikit-learn, Spark, etc.)
Transfer learning and meta-learning
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.