Marinka is a postdoctoral research fellow in Computer Science at Stanford University where she works with Jure Leskovec and collaborates closely with major biomedical research departments worldwide. I am also a Chan Zuckerberg Biohub postdoctoral researcher.
Her research investigates machine learning for biomedical sciences, focusing on large networks of interactions between biomedical entities--e.g., proteins, drugs, diseases, and patients. She leverages these networks at the scale of billions of interactions among millions of entities and develops new methods blending machine learning with statistical methods and network science.
She uses her methods to answer burning scientific questions, such as how Darwinian evolution changes molecular networks, and how data-driven algorithms can accelerate scientific discovery.
She uses her methods to solve high-impact problems that serve as a first step to bridging the divide between basic science and patient data, such as what drugs and combinations of drugs are safe for patients, what molecules will treat what diseases, and how newborns are transferred between hospitals and how these transfers influence outcomes.
Marinka received a Ph.D. in Computer Science from the University of Ljubljana in 2015 while also researching at Imperial College London, University of Toronto, Baylor College of Medicine, and Stanford University. She obtained a B.Sc. in Computer Science and Mathematics in 2012.
Marinka is named a Rising Star in EECS by MIT and honored to be one of the Next Generation in Biomedicine by The Broad Institute of Harvard and MIT!
Marinka will be moving to Harvard University, where her research will focus on Artificial Intelligence for Science, Medicine, and Health. She is looking for outstanding students and postdoctoral fellows who would like to join her in transforming science and medicine to data-driven and computationally enabled disciplines.
The research focus is on new data science and machine learning methods for learning and reasoning over rich interaction data and on the translation of these methods into solutions for biomedical problems. This scientific approach not only opens up new avenues for understanding nature, analyzing health, and developing new medicines to help people but can impact on the way predictive modeling is performed today at the fundamental level.
Marinka Žitnik, ASEF Global Fellow in 2014 and soon to become a professor at Harvard University. She was chosen among 400 candidates. Congratulations Marinka!
Read an interview with Marinka, published by Slovenian newspaper Delo.