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Department of Mathematics

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At present the most developed part of the research activity of the Department of Mathematics can be characterized as Pure Mathematics, Applied Mathematics, Statistical Sciences, Actuarial Science and Financial Mathematics. Following are the list of the researchers and their area of interests of our department.

Recently, the Department of Mathematics begun to be involved into the research in the area of Mathematical Education and we will update the information here soon.

Name of the Faculty Members

Research Interests
Dr. Nagarani Ponakala Physiological Fluid Dynamics, Non-Newtonian Fluids, Computational Methods, Non-linear Differential Equations, Special Functions and Applications.
Dr. Mahesha Narayana Computational Methods, Fluid Mechanics.

Dr. Tamika Royal-Thomas

Longitudinal Data Analysis, Early Life Predictors of Cardiovascular Disease, Factor Analysis, Principal Component Analysis, Survival Analysis.
Dr. Diptiranjan Behera Fuzzy and Interval Mathematics, Computational Methods, Fractional Differential Equations, Non-Linear Differential Equations, Structural Analysis, Optimization Problems.
Dr. Kirk Morgan Stochastic Difference Equations, General Relativity.
Mr. Ajani Ausaru Biomechanics
Mr. Howard Hines Reduction of Climate Risks to Industry and Livelihoods, Research on Health Insurance
Dr. Nordia Thomas Market Microstructure, Fintech, Financial taxation, Financial Regulation.
Mr. W. St. Elmo Whyte Stochastic Processes, Enterprise Risk Management
Prof. Alexandra Rodkina Asymptotic Behavior of Solutions of Nonlinear Stochastic Functional-Differential and Difference Equations, Stability of Numerical Methods for Nonlinear Stochastic Equations, Applications in Mechanics, Engineering, Mathematics of Finance, Risk Theory.


Explanation of some of the active research areas in the department are as follows.

  • Stochastic Differential and Difference Equations

Stochastic equations are used to model real-world systems that are subject to interference in the form of randomexternal perturbations or feedback noise. This interference can have a dramatic qualitative effect on these systems and should therefore be included in any analysis of their behaviour. For example population models may be designedto reflect the unpredictable effects of disease and environment, as well as classical predator-prey, birth-death dynamics.

This work is lead by Prof. Rodkina. 


  • Physiological Fluid Dynamics

Physiological fluid dynamics involves the study of idealized model problems (either experimental or theoretical) that characterize the key features of flows in the body. Being an interdisciplinary subject, its development is due to the close interaction between engineers, mathematicians, physicists, biologists and physiologists. Mathematical models have proved to be powerful tools for understanding not only the normal, but also the pathological conditions of the physiological systems. The information gained from such studies has contributed to the improved efficiency
  • in the diagnosis of various arterial diseases,
  • the appraisal of newly found treatment procedures,
  • designing of artificial organs.
Some of the models that have gained lot of interest to understand the physiological systems are
  1. Modelling of flow in stenosed arteries;
  2. Modelling of flow in catheterized vessels;
  3. Modelling of Dispersion/Transport phenomena in cardiovascular system;
  4. Modeling Peristaltic transport in physiological fluids.
The objective of these models is to understand the physiological process through mathematical models and fluid dynamic principles and the results obtained from these mathematical models compare with the experimental or measured results. This research is lead by Dr. Ponakala and hear team including PhD students and several international collaborators. 


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