Assistant Professor at The University of New Mexico
Chapel Hill, North Carolina, United States
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Summary
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Senior
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Miheer Dewaskar is an Assistant Professor and applied statistician with 12 years of experience developing robust, interpretable inference tools at the intersection of mathematics, statistics, and computation. Trained at Chennai Mathematical Institute and UNC Chapel Hill, he built novel methods to fit misspecified parametric models while automatically detecting outliers and to extract clusters and uncertainty from nonparametric Bayesian density posteriors. His recent work focuses on fast approximate fitting of discrete Bayesian models to massive continuous datasets, motivated by large-scale brain-imaging applications that require compressing observations into a finite number of support points. At Duke he translated these methodological advances into practical algorithms and now continues this work at the University of New Mexico, blending theoretical rigor with computational scalability. Colleagues appreciate that he combines deep probabilistic thinking with a knack for turning complex models into usable tools.
12 years of coding experience
3 years of employment as a software developer
Bachelor and Master of Science - BS & MS, Mathematics and Computer Science, Bachelor and Master of Science - BS & MS, Mathematics and Computer Science at Chennai Mathematical Institute
Doctor of Philosophy - PhD, Department of Statistics and Operations Research, Doctor of Philosophy - PhD, Department of Statistics and Operations Research at University of North Carolina at Chapel Hill
Finding communities in a bipartite correlation network
Contributions:4 releases, 158 commits, 26 PRs in 3 years 1 month
bipartite
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