Erkan O. Buzbas

• Theoretical Population Genetics
• Meta-Research
• Computational Methods
• Bayesian Statistics

After completing my PhD with Prof. Paul Joyce at the University of Idaho, I worked at the University of Michigan and at Stanford University as a postdoctoral fellow under the supervision of Prof. Noah Rosenberg. My work on theoretical population genetics and meta-research are interdisciplinary and I collaborate with faculty from natural, social, mathematical sciences, and humanities.

• E.O. Buzbas. On 'Estimating species trees using approximate Bayesian computation', Molecular Phylogenetics and Evolution, 65: 1014-1016
• Paul Joyce, Alan Genz and E.O. Buzbas. Efficient simulation methods for a class of nonneutral population genetics models. Journal of Computational Biology, 19: 650-661.
• E.O. Buzbas, P. Joyce and N.A. Rosenberg. Inference on balancing selection for epistatically interacting loci. Theoretical Population Biology, 79: 102-113, Issue 3.
• Mosher, J.T., Pemberton, J.T., Harter, K., Wang, C., Buzbas, E.O., Dvorak, P., Simón, C., Morrison, S.J. and Rosenberg, N.A. “Lack of population diversity in commonly used human embryonic stem-cell lines.” New England Journal of Medicine, 362: 183-185.

My work in theoretical population genetics involves developing mathematical models of evolution at the population level and computational statistical methods to perform inference from these models. A particular focus area has been devising statistical methods that are scalable to complex models. My work in meta-research involves creating a meta-scientific framework to gain insight into the process of scientific discovery and issues surrounding reproducibility in science. This is a long-term research program that will investigate the process of scientific discovery from diverse perspectives, using modern philosophy of science and statistics, mathematical modeling, and computational methods.