Statistics, biostatistics, bioinformatics, genomics, Bayesian statistics, statistical methods for data science and big data.
My research areas focus on developing Bayesian statistical methods for genomics, bioinformatics, data science and big data. This includes integrating multiple sources of genomic information into statistical models, such as expression, DNA sequence and functional data. Other work involves determining Bayesian models for gene expression meta-analysis, and comparative genomics approaches to identifying genetic regulatory networks in prokaryotic species.
Learn more at www.math.umass.edu/~conlon
- BS Mathematics, University of Wisconsin, Madison
- PhD Biostatistics, University of Minnesota
- Postdoctoral training: University of Washington, Seattle
- Postdoctoral training: Harvard University