My broad research focus is on the development – or apt and meaningful use – of statistical and computational methodologies for data-intensive science. Predominantly, my focus has been astrostatistics (radio astronomy in particular). In the past, I have dabbled into computational biology – genomic sequence analysis in particular.

Many fields of knowledge – sciences in particular – have grown increasingly data-rich over the past few decades. The complexity of scientific questions being addressed has also increased rapidly. Indeed, 21st century science has been aptly described as "large data sets, complex questions" science by Bradley Efron.

The use of statistics is inevitable because of the inherent uncertainties in data, whereas computation is unavoidable because of data size, methodological intricacies, and model complexity. What often helps address complex problems is fresh ways of looking at the problem and the available data, coupled with apt use of statistical and computational methodologies.

My approach and outlook is imminently inter-/multi-disciplinary (where problems are domain-specific, and the methodologies are statistical and computational) and problem-centric (where methods are devised or adopted to suit the problem being addressed, and not vice versa).