Fangfang Xia is a Computer Scientist in the Computing, Environment and Life Sciences Directorate at Argonne National Laboratory and a Fellow in the Computation Institute at The University of Chicago. His research combines bioinformatics, machine learning and high performance computing to design and build efficient systems for genomic analysis. In particular, he is interested in genome assembly, annotation, modeling and precision medicine.
Xia is currently involved in three primary projects: (1) exascale deep learning enabled precision medicine for cancer with researchers at Argonne, Los Alamos, Lawrence Livermore and Oak Ridge National Labs and the National Cancer Institute, (2) development of bioinformatics algorithms and services for the NIH/NIAID Pathosystems Resource Integration Center (PATRIC) with researchers at Fellowship for Interpretation of Genomes and Virginia Biocomplexity Institute, and (3) end-to-end genome annotation and phenotype prediction with deep learning.
Xia received his Ph.D. in computer science from University of Chicago in 2010. He was a computational postdoctoral fellow at Argonne from 2010 to 2012 and was promoted to assistant computer scientist in 2012 and computer scientist in 2016.
- Computational models for predicting drug responses
- Large-scale genome and metagenome assembly
- Antimicrobial resistance detection and prediction
- High-throughput reconstruction of genome-scale metabolic models
- Genome annotation, comparative genomics and phenotype prediction
- High performance computing
- Machine learning