While he has been working on a broad range of topics in Computer Science, his chief research interest is in Software Engineering, in particular Big Data Software Engineering including software maintenance and evolution. As co-lead of the "Cloud platform for genomic-phenomic analysis," his research is focused on establishing a high-speed, large-scale, hybrid-cloud infrastructure to support crop phenomics research. As part of this, he is interested in exploiting well established Big Data frameworks, Big Data analytics techniques, state-of-the-art cloud technologies, and high-speed processing pipelines towards analyzing, modeling, visualizing and exploring petabytes of heterogeneous types of crop phenotype data.