Probabilistic modeling in biological and medical informatics

Berkeley Annual Research Symposium (BEARS) 2019

Yun Song


Technological advances over the past decade have led to an explosion in biomedical data, providing unprecedented opportunities to understand fundamental biological processes and to foster public health.  In this talk, I will highlight the important role of probabilistic modeling in making inference from multi-faceted biological data which are often complex and messy.


Yun S. Song is a professor of EECS and Statistics. He received the BS degrees in mathematics and physics from MIT, and a PhD in physics from Stanford University. After his PhD, he spent a year at the Mathematical Institute at the University of Oxford, where he decided to change fields. He became a postdoctoral researcher in the Department of Statistics at Oxford, and started doing research in computational biology and mathematical population genetics. From 2004 to 2007, he was a postdoctoral researcher at UC Davis in the Department of Computer Science, and the Section of Evolution and Ecology.