Research team


As an applied mathematician, I have a diverse set of skills and experience that I have applied to a wide range of projects. One area of focus that I have been particularly interested in is the development of mathematical models to study complex systems. My expertise in mathematical modeling, data analysis, and computational methods has enabled me to make significant contributions to the field of immunology and other related fields. One example of my work is the development of mathematical models using ODEs and PDEs to study the dynamics of cellular populations. I have applied these models to study the mechanisms that govern the dynamics of T cells and B cells in the immune system. I have also used these models to study other systems such as viral infections, cancer dynamics, and population dynamics. To create these models, I used a combination of analytical and computational techniques, including numerical simulations and data-driven computational methods. I also used real data to validate and optimize the models. I have experience with programming languages such as Python, R, SAS and Matlab, as well as high-performance computing to handle large-scale simulations and data analysis. Throughout my work, I have collaborated with other scientists, including biologists, epidemiologists and physicians, to gather information and insights that helped me improve the models. I have also communicated my findings and results to the team and other researchers in the field through presentations and publications. In addition to my expertise in mathematical modeling and data analysis, I also have strong skills in machine learning, deep learning, optimization techniques and system dynamics. I am always eager to apply my skills and knowledge to new and challenging projects and to make a meaningful.