Kashif's prime interest is to investigate the genome structure and composition of complex polyploidy grasses that help in understanding their evolutionary directions towards domestication. He is trying to demarcate the genes involved in the sustainability of several stress-resistant wild grasses, which could be instigated in domesticated plants. He has been working on genomics for a decade, spending time at the Max Planck Institute in Germany and the University of Experimental Botany in the Czech Republic. He has been involved in the genome assembly of chickpea (Cicer arietinum) done at NIPGR, India.

He essentially loves to play with big data generated from cells, especially NGS data. He contemplates his expertise as helping to connect biology with bioinformatics, and trying to solve the data-driven problems for a biological system. Apart from running pipelines, he focuses more on what the final visualization from data is trying to say in terms of new discoveries and significance.

Besides performing bioinformatics analysis and code writing in R and Python, Kashif is ardent about the different effective ways to convey scientific findings to diverse audiences. This includes mainly the use of common metaphors to relate his message, the inclusion of several variables in one graph to make it more informative (same time not increasing its complexity), and overcoming the art of writing so that his findings look more appealing and comprehensive.