Research Bio
Yun S. Song is a professor of EECS and Statistics. His research group primarily consists of computer scientists, statisticians, and mathematicians who are fully committed to advancing biology. They develop AI/machine learning models and robust statistical methods to facilitate the research of the broad biomedical community, while also getting deeply involved in data analysis to help make new biological discoveries. His current research interests include language models of biological sequences, variant effect prediction, single-cell genomics, metagenomics, structural biology, and immunology.
His awards and honors include the NIH Pathway to Independence Award K99/R00, Alfred P. Sloan Research Fellowship, Packard Fellowship for Science and Engineering, NSF CAREER Award, Jim and Donna Gray Faculty Award for Excellence in Undergraduate Teaching, Miller Research Professorship, Math+X Simons Chair, and Chan Zuckerberg Biohub Investigator Award.
Research Expertise and Interest
artificial intelligence, machine learning, applied probability and statistics, computational biology, computational genomics, human genetics
In the News
CZ Biohub awards nearly $14.5 million to Berkeley researchers
Genome Analysis Pinpoints Arrival and Spread of First Americans
The original Americans came from Siberia in a single wave no more than 23,000 years ago, at the height of the last Ice Age, and apparently hung out in the north – perhaps for thousands of years – before spreading in two distinct populations throughout North and South America, according to a new genomic analysis.
Teaching
Supervised Independent Study [COMPSCI 199]
Individual Research [COMPSCI 299]
Professional Preparation: Supervised Teaching of Computer Science [COMPSCI 399]
Discrete Mathematics and Probability Theory [COMPSCI 70]
Individual Study Leading to Higher Degrees [STAT 299]
Supervised Independent Study [COMPSCI 199]
Individual Research [COMPSCI 299]
Directed Study for Graduate Students [STAT 298]
Individual Study Leading to Higher Degrees [STAT 299]
Supervised Independent Study [COMPSCI 199]
Field Studies in Computer Science [COMPSCI 297]
Individual Research [COMPSCI 299]
Field Study in Statistics [STAT 197]
Individual Study Leading to Higher Degrees [STAT 299]
Individual Study Leading to Higher Degrees [STAT 299]
Algorithms for Computational Biology [CMPBIO 276]
Algorithms for Computational Biology [CMPBIO C176]
Supervised Independent Study [COMPSCI 199]
Individual Research [COMPSCI 299]
Professional Preparation: Supervised Teaching of Computer Science [COMPSCI 399]
Algorithms for Computational Biology [COMPSCI C176]
Senior Honors Thesis Research [COMPSCI H196A]
Individual Study Leading to Higher Degrees [STAT 299]