My Research Highlights

My research spans on opportunities at the intersection of data science, computation, and biology. I have a broad range of computational modeling experience in diverse domains ranging from engineering, automation, medical diagnostics, agriculture, immunology, bioinformatics, epidemiology, and regulatory genomics. Over the period of last ten years, the primary focus of my research has been computational biology and bioinformatics. The following sections sketch some of the work in these areas that I have recently been involved in with colleagues, mentors, and the collaborators.

 

My primary research focuses on understanding the rich contextual information associated with most data sets in a variety of real-world domains and using it to infer complex patterns. A brief synopsis of my research work include:

 

  • Designing efficient inference and knowledge extraction pipelines for the models capable of handling uncertainties and interdependencies among large-scale data sets, a characteristic that is predominantly associated with large scale biological data sets.  

  • Using a combination of modern analytical and machine learning  skills for extracting the rich contextual information associated with complex data sets.

  • Computational modeling and analysis of disparate data sets, such as electronic health records, scientific texts, and high-throughput experiments.

  • Developing bioinformatics strategies for mapping and understanding the interplay of genetic and environmental mechanisms of human disease.

  • Investigating the multidimensional and integrated molecular data to understand the biological mechanism and the etiology of the diseases.

  • Inferring the causes and consequences of environmental insult on human health with emphases on neuropsychiatric and infectious diseases.

  • Connecting the dots from climate observations to disease prevalence with an overarching goal to formulate testable hypotheses from epidemiological data.

"Progress is made by trial and failure; the failures are generally a hundred times more numerous than the successes ; yet they are usually left unchronicled."
William Ramsay (1852-1916)
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© 2020 by Atif Khan