Applied Mathematics

The research in the lab in divided into 4 main domains:

A) Mathematical immunology.

We study the adaptive immune response through the repertoire of expressed receptors and the repertoire of expressed epitopes. We use machine learning tools to compute predicted (mainly CD8 T cell) epitopes and the relation between the presentation of these epitopes on viruses and cancer cells and the evolution of viral/tumor population.

We use tools from ecology and evolution to understand the diversity of the human B and T cell response and the relation between this diversity and the immune response to pathogens. This analysis is performed in collaboration with leading labs in Europe and the US.

B) Population dynamics.

We study stochastic population dynamics of meta populations. This analysis is mainly focused on the human HLA locus. We study the population genetics of human sub-population and the selection forces affecting HLA alleles and haplotypes. This is performed in collaboration with the NMDP.

C) Stochastic processes.

We study spatially extended birth death processes and the macroscopic effect of fluctuations on ecological and financial systems.

D) Meta data based machine Learning

We use machine learning to extract information on processes from meta data. A main focus of this research is to extract information on the content of nodes from network attributes.