My primary research focuses on the data mining opportunities at the intersection of engineering, computation, and biology. Throughout my career, I have tried to define my research interests by the demands of health care and how they could be satisfied by the modern computing approaches. A brief summary of my research interests includes: 

Designing efficient inference and machine learning pipelines for the models capable of handling uncertainties and interdependencies among large-scale data sets.

Using 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 genomic 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 the infectious diseases. 

Connecting the dots all the way from climate observations to disease prevalence with overarching goal to formulate testable hypotheses. 

Khan AA, Katanic D, Thakar J. “Meta-analysis of cell-specific transcriptomic data using fuzzy c-means clustering discovers versatile viral responsive genes.” BMC bioinformatics. Jun 2017 6;18(1):295. 

Katanic D, Khan AA, Thakar J, “PathCellNet: Cell-type specific pathogen-response network explorer.” Journal of Immunological Methods, Dec 2016 31;439:15-22. 

Piepenbrink MS, Samuel M, Zheng B, Carter B, Fucile C, Bunce C, Kiebala M, Khan AA, Thakar J, Maggirwar SB, Morse D, Rosenberg AF, Haughey NJ, Valenti W, Keefer MC, and Kobie JJ, “Humoral dysregulation associated with increased systemic inflammation among injection heroin users.” PLOS ONE. Jul 2016 5;11(7):e0158641.  

Rebhahn JA, Roumanes DR, Qi Y, Khan AA, Thakar J, Rosenberg A, Lee F, Quataert SA, Sharma G, and Mosmann TR, “Competitive SWIFT cluster templates enhance detection of aging changes.” Cytometry Part A, Jan 2016; 89(1):59-70.

Khan AA, Iliescu DD, Sneath RJ, Hutchinson CE, and Shah AA, “Principal component and factor analysis to study variations in the aging lumbar spine.” IEEE journal of biomedical and health informatics (J-BHI), Special Issue: Bioinformatics in Clinical Environments, Mar 2015;19(2):745-751. 

Chair Special Session: Intelligent Bioinformatics in the Era of Big Data

                        - International Conference on Intelligent Systems Design and Applications (ISDA 2017), 14-16 December 2017, Delhi, India.

Member Technical Program/Review Committee  

Reviewer of Scientific Journals