Valentina Boeva, Prof. Dr.

Address:
ETH Zurich
Prof. Dr. Valentina Boeva
CAB F51.2
Universitatstrasse 6
8092 Zurich
Switzerland

Phone:
+33 (0) 1 44 41 23 89

Research area

Rapid advancements in data analytics in recent years, coupled with development of novel tools for molecular profiling of cancer tissues provide new opportunities to better understand the mechanisms of tumorigenesis. This is achieved via learning from so-called "omics" data (genomic, transcriptomic, proteomic, metabolic, etc.) to extract biomarkers of survival and response to treatment. We see various techniques, both classical statistical methods, as well as more advanced machine learning tools, being increasingly effective in extracting these biomarkers and thus improving clinical decisions.

Valentina Boeva centers her research on multi-omics data integration and develops methods for omics data analysis with a specific focus on biological questions that have the potential to influence the current practices to treat cancer.

She expects a two-fold benefit from the computational methods she develops. First, the application of our methods to cancer datasets will result in a deeper understanding of biological processes driving tumor progression. Second, she expects to obtain genetic or transcriptional biomarkers integrated into supervised machine learning models to be used in clinics for patient risk stratification and therapeutic guidance. All software Valentina and her group develop is open-source.

CV

  • since 2019: Assistant Professor of Computational Cancer Genomics, ETH Zurich, Switzerland
  • 2016 - 2019 Group Leader, Cochin Institute / Inserm / CNRS / Paris Descartes University, France
  • 2011 - 2016 Research Scientist, Curie Institute / Inserm / Mines ParisTech, France
  • 2008 - 2010 Postdoctoral Researcher, Curie Institute / Inserm / Mines ParisTech, France
  • 2007 - 2008 Postdoctoral Researcher, Ecole Polytechnique and INRIA Rocquencourt, France
  • 2007, Ph.D. degree, Department of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow, Russia
  • 2003, Master's degree in Mathematics and Applied Mathematics, Department of Mechanics and Mathematics, Lomonosov Moscow State University, Moscow, Russia

Complete list of publications: Link

Teaching (Links to the ETH Course Catalogue):

Fall semester 2021:
Spring semester 2022:
Fall semester 2022: