Bioinformatician, Single-cell data analysis, Computational immunology, Genome-scale metabolic modeling.

Shawez Khan obtained his first Master (Bioinformatics) in 2010 from India and his second Master (Systems and Synthetic Biology) in 2016 from France. He received his Ph.D. in Bioinformatics from KU Leuven, Belgium in 2019. During his Ph.D., he mainly worked on the re-use of publicly available transcriptomics data and genome-scale metabolic modeling of endothelial cells to identify novel anti-angiogenic metabolic targets. Shawez is interested in gene expression analysis, constraint-based modeling and Public data mining. 

Throughout his Ph.D., Shawez handled a variety of multi-omics datasets of cancer patients and specialized in applications of transcriptomic analysis related to anti-angiogenic metabolic targets. Afterward, his first career at CCIT, Herlev Hospital, Denmark, enabled him to build skills in analyzing and interpreting the single-cell multi-omics data (in-house and public) generated from cancer patients of diverse solid tumors to access the functional heterogeneity of tumor-infiltrating lymphocytes (TILs). 

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