Mathematics & Statistics Faculty and Staff

Research interests:My research interest focuses on the methodological developments in heterogeneous dependence modeling in multivariate data.My current research areas are longitudinal data analysis, statistical learning/machine learning, dynamic data science, spatial/spatio-temporal models, mixed models, copulas, missing data analysis, measurement error, statistical computing, meta-analysis and time series analysis.I am also working on several interdisciplinary areas including computational finance, transportation, electricity demand, supply chain, environment, medical & health research etc.

My research is in combinatorics on words, an area that lies at the border of mathematics and theoretical computer science. I am primarily interested in long strings over small alphabets — which patterns can be avoided and which must inevitably occur? I use a mix of mathematical proof and computation to establish new results related to pattern avoidance.

My research interest is in statistical machine learning, Bayesian statistical inference, and statistical ecology. The main focus of my research is in developing ensemble method to improve its prediction performance by exploiting the richness of useful variables in high-dimensional data to identify important models and variables, and therefore to answer important research question. I have shown applications of my methods in (i) drug discovery to detect drug like active bio-molecules for development and (ii) protein homology to detect homologous proteins and produce evolutionary sequences of proteins. These days, I am focusing more on developing Bayesian and computational models for ecology, health care, housing markets and genetics data.