My background is in database and knowledgebase systems, with an expertise in bioinformatics and computational biology. My current research focuses on large data management, data integration and interoperability, linked and graph data management, and query language design, for applications in social networks, life sciences, earth sciences, and educational technology for online learning. My primary research focus is on developing collaborative computing platforms for integrated large and heterogeneous earth sciences data in support of the Northwest Knowledge Network (NKN) initiative (a University of Idaho (UI), Idaho National Laboratory [INL], and USGS joint initiative for gathering, accessing and using cross-disciplinary data for earth sciences and climate research). In recent years, I have intentionally re-focused my research interests on the growing field of Data Science and Analytics in collaboration with colleagues in mathematics and statistics at UI. My goal is to leverage my past research experience and publication record in these areas to establish an extramurally funded, nationally and internationally visible research program in large linked data management.
The multi/inter-disciplinary nature of my research is evident in my collaborations throughout my career. I collaborate with ecologists and environmental scientists at the University of Idaho, University of Montana and Oregon State University; and educationists at the Oregon State University and the University of Idaho. I also collaborate with computer scientists at the University of Michigan, University of North Carolina at Greensboro and University of Texas at Dallas; and life sciences researchers at Wayne State University Medical School. These collaborations are the premise of my basic computer science research that includes graph modeling and analysis, ontology and schema matching, visual language and querying, query language design, data integration and analytics orchestration and knowledge representation. In all these projects, the main vehicles I utilize include smart knowledge representation, declarative query languages and graph data models to design autonomous large data management and querying systems for BigData end users.
My projects have been funded by research grants from the National Science Foundation, the National Institutes of Health and US Department of Agriculture throughout my professional career and made it possible for me to deliver online research systems such as LifeDB, mir-AT, MapBase, PhyloBase, VisFlow, and MindReader for public use.
My research program is complemented by a focused initiative to reintroduce a stream of database systems courses in our Department at UI to strengthen our undergraduate and graduate curriculum. At UI, I have designed first and advanced database courses, and a research course. Additionally, I am currently developing two new graduate courses on graph data management and data interoperability. Through a recent multi-university $16 million NSF EPSCoR Collaborative grant, the addition of a new database faculty with expertise in geographical data management and application design has not only increased course choices in databases and data science for undergraduate and graduate students but along with my own expertise in bioinformatics and BigData, has substantially increased collaborative research in big data management.
My research interests can be categorized into four broad application areas:
Almost all the projects leverage my research in BigData. The nascent Data Science focus of my research explores ways to orchestrate analytics using a series of natural language instructions over BigData repositories. Details on these projects are available in the Research Projects page.