CIS - "Get to know your neighbors" Seminar series - Prof. Maria Brbic

Thumbnail

Event details

Date 30.01.2023 15:1516:15  
Speaker Prof. Maria Brbic
Location Online
Category Conferences - Seminars
Event Language English
Title: Machine learning methods for biomedical discovery

Abstract
Biomedical data poses multiple hard challenges that break conventional machine learning (ML) assumptions. Biomedical data are heterogeneous, originate from different experimental conditions, and collecting high-quality labeled datasets is often impossible. In this talk, I will highlight the need to transcend our prevalent machine learning paradigm and methods to enable them to become the driving force of new scientific discoveries. I will present machine learning methods that have the ability to bridge heterogeneity of individual biological datasets by transferring knowledge across datasets with an unique ability to discover novel, previously uncharacterized phenomena. I will discuss the biological findings enabled by these methods and the conceptual shift they bring in annotating comprehensive single-cell atlas datasets.

Bio
Maria Brbic (https://brbiclab.epfl.ch/) is an Assistant Professor of Computer Science and, by courtesy, of Life Sciences at the Swiss Federal Institute of Technology, Lausanne (EPFL). She develops new machine learning methods and applies them to advance biology and biomedicine. Her methods have been used by global cell atlas consortia efforts aiming to create reference maps of all cell types with the potential to transform biomedicine, including the Human BioMolecular Atlas Program (HuBMAP) and Fly Cell Atlas consortium. Prior to joining the EPFL faculty in 2022, Maria was a postdoctoral fellow at Stanford University, Department of Computer Science where she worked with Jure Leskovec and was a member of the Chan Zuckerberg Biohub at Stanford. Maria received her Ph.D. from University of Zagreb in 2019 while also researching at Stanford University as a Fulbright Scholar and University of Tokyo. She was named a rising star in EECS by MIT in 2021.

 
The CIS seminar will take place In hybrid mode: Room INF 328 and by Zoom https://epfl.zoom.us/j/63769787330

Please connect to your zoom account using your "@epfl.ch" address, as this live event is only open to the EPFL community
Monday, January 30th, 2022 from 3:15 to 4:15 pm
NB: Video recordings of the seminars will be made available on our website and published on our social media pages

Practical information

  • General public
  • Free

Organizer

  • CIS

Contact

Tags

CISSBSTIICENACApprentissage automatique Intelligence artificielle Robotique Vision par ordinateur Artificial intelligence AI Robotics Computer vision

Share