Bio-Mathematics/Statistics Interests:

Mathematical Biology is an active and growing research area in general. My research interests in Mathematical biology focus Mathematical immunology, epidemiology, spatial ecology and population dynamics. I am interested in using theoretical, statistical and computational techniques to understanding the evolution and spread of diseases and controlling their extinctions. I embrace a multidisciplinary approach to problems, employing microbiological research, behavioral and social science, network analysis, mathematical modeling, computer simulations and theoretical frameworks.

Areas of Interest:

Mathematical Epidemiology: It involves the development of mathematical models for studying the dynamics of infectious disease transmission and epidemics, and for evaluating the potential impact of interventions for control and prevention. Diseases may range from infectious pathogens such as HIV, malaria and influenza, to obesity and diabetes.

Mathematical Immunology: Current cancer therapies predominantly focus on surgery, chemotherapy and radiotherapy, each of which carries major side effects for the patient. Because cancer cells are not easily distinguishable from normal cells, the immune system is not always efficient in providing an adequate response to cancerous growth. Recently, there has been increased interest in improving the ability of the immune system to target tumors. This research highlights how mathematical models could help provide more understanding and insights of cancer-immune system interactions.

Computational Biology: This research area uses computational biology approaches to understand the complexities of the recognition and control of infectious diseases by the immune system. Computational biology is an interdisciplinary field that applies the techniques of computer science, applied mathematics, and statistics to address biological problems. Advances in technology over the past decade enable more in-depth studies of biological systems through the generation of an enormous volume of experimental data. Computational biology approaches are required to analyze and interpret this data.

Complex Systems: The Complex Systems in Biology research area aims to understand the basic dynamics and pathogenesis of these infections, how the immune system interacts with them, and ultimately how we can control them. To achieve this we apply computational and mathematical approaches to understanding and predicting the complex interactions between host and pathogen. These interactions range from the molecular level (how immune molecules such as the T cell receptor interact with viral molecules), through to the dynamics of infection within individual hosts, and finally to the level of the host and pathogen population. Some of the chronic infectious agents’ research includes breast cancer, HIV, malaria, and tuberculosis.

Mathematical Ecology: Basically, I use mathematical and statistical methods and models to explore ecological questions. Specifically, I am interested in interactions between and among species and their spatial heterogeneity that affect population dynamics (growth, reproduction, spread) and community dynamics (diversity, competition).

Interesting Research Topics

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