This fall we are welcoming Dr. Sedi Bartz to the Department of Mathematical Sciences. Dr. Bartz’ research focuses on topics of nonlinear analysis and variational analysis. He develops refinements of abstract convex analysis, and in turn, transforms his refinements into a unifying language for phenomena in variational analysis which used to be considered quite apart. Dr. Bartz is also a specialist in classical convex analysis and monotone operator theory, theories which are among the most popular tools of modern optimization.
Dr. Bartz holds a Ph.D. from The Technion-Israel Institute of Technology. He arrives to UML after a 3 year term as a Post-Doctoral Fellow at the University of British Columbia, Kelowna, Canada.
This fall, we are happy to welcome Dr. Nilabja Guha to the Department of Mathematical Sciences. Dr. Guha is a statistician who was at Texas A&M University in a postdoctoral position prior to joining UML. He received his doctoral degree in statistics from the University of Maryland Baltimore County where his adviser was Dr Anindya Roy.
Dr Guha’s research interest include Bayesian Modeling, Inverse problems, Uncertainty Quantification, High-dimensional Problems and Graphical Modeling.
Some of his recent publications are
- Guha, Nilabja, Anindya Roy, Yaakov Malinovsky, and Gauri Datta., 2016. An optimal shrinkage factor in prediction of ordered random effects. Statistica Sinica 26: 1709-1728.
- Guha, N. and Tan, X., 2017. Multilevel approximate Bayesian approaches for flows in highly heterogeneous porous media and their applications. Journal of Computational and Applied Mathematics, 317, pp.700-717.
- Yang, K., Guha, N., Efendiev, Y. and Mallick, B.K., 2017. Bayesian and variational Bayesian approaches for flows in heterogeneous random media. Journal of Computational Physics, 345, pp.275-293.