Department of Mathematics
and Statistics

Mathematics and Science Center, Room 368
146 Library Drive
Rochester, MI 48309-4479
(location map)
phone: (248) 370-3430
fax: (248) 370-4184

Monday–Friday: 8:00–11:59 a.m. and 1:00–5:00 p.m.


Areas of Research

Members of the Department of Mathematics and Statistics are actively engaged in research in many areas of Mathematics and Statistics. While the research interests of some of the members crossover into different branches of mathematics, below is a general division of the research groups.

To learn more about past and ongoing math research, request the full Academic Genealogy of the Oakland University Department of Mathematics and Statistics and the Collaboration graphic among tenure-track faculty members here at any time in the period 2003-2012 from Denise Diebold through or (248) 370-3431.

Mathematical Biology
Number Theory
Faculty Awards
Aycil Cesmelioglu

National Science Foundation award (2021)

"Collaborative Research: Development of Reduced Order Models for Poroelasticity and Related Problems"

Poroelasticity is a framework of continuum mechanics models for problems involving a porous elastic medium and a fluid flow. Poroelasticity problems have real-world applications such as hydrocarbon extraction in petroleum engineering, physiological processes such as the blood flow in the human body, groundwater contamination in environmental engineering, and modeling magma and mantle migration in geophysics. There is a real need to obtain high-resolution numerical solutions for the poroelasticity but these require large computational resources, even with theoretically optimal algorithms. This project will develop methods that can provide high accuracy solutions for large poroelasticity problems with feasible computational costs.
Nghia Tran

National Science Foundation award (2018)

"Collaborative Research: Second-Order Variational Analysis in Structured Optimization and Algorithms with Applications"

In this project, Prof. Tran focuses on developing advanced tools of mathematical analysis to investigate modern structured optimization problems and designing new efficient algorithms to solve them. These problems arise in different areas of science and engineering, including massive data analysis, machine learning, signal processing, medical image reconstruction, statistics, traffic networks, and operations research. Most of them share the irregular phenomenon of nonsmoothness or nonconvexity that challenges computation. His approach will be mainly based on a relatively young subfield of applied mathematics, variational analysis, which is naturally compatible with these nonsmooth and complex structures.


Dan Steffy

A research project funded by Ford (2018)

(Previous awards information will be added soon.)