"At the moment, I am working in the field of bioinformatics on ancestral sequence reconstruction using stochastic processes. In this regard, computational genomics, stochastic processes and optimization is my specialty. In addition, I am also interested in working in deep learning, neural networks and biomedical informatics domains as well as image processing, text mining, recommender system, and social networks."
Thesis: Frequentist Estimation of Evolutionary History of Sequences with Substitutions and Indels
Keywords: ancestral sequence reconstruction, multiple sequence alignment, Poisson indel process
Abstract: The evolutionary history of molecules is described by a tree structure called phylogeny, which is inferred from genomic sequences. Phylogenies are used for testing biological hypotheses with applications ranging from medicine to ecology. Inferring ancestral molecular states on phylogenetic trees can help us in testing such hypotheses. Phylogenetic inferences typically rely on character substitution models that describe only point mutations, but ignore insertions and deletions. The goal of this project is to develop a new maximum likelihood method for ancestral sequences reconstruction that accommodates insertions and deletions, and therefore is more biologically meaningful.
Planned Duration: 11/2019 - 11/2023