Dr. Kumar Mainali

Data Science Lead/Senior Data Scientist

Kumar is the Data Science Lead/Senior Data Scientist at the Chesapeake Conservancy. Kumar obtained a PhD in Ecology and a Masters in Statistics, both from The University of Texas at Austin. He then joined Bill Fagan’s lab in the University of Maryland as a postdoctoral associate. His research career collectively includes projects in conservation biology, ecology, biogeography, climate change, human microbiome, behavior and remote sensing. A unifying theme in Kumar’s research projects is the application of sophisticated statistical and mathematical tools in understanding processes, patterns and mechanisms. Many of his projects include application of machine learning algorithm for predicting species distribution. He has used multivariate methods of classical statistics in many applied ecology projects. He enjoys working on novel application of mathematical/statistical tools in a new way of understanding a system (e.g, using causal models in detecting species interaction in human microbiome). He deeply enjoys developing new statistical metrics and tools to quantify ecological processes by using mathematical tools. However, he finds working on burning issues of conservation and environment most rewarding; he uses a suite of methods including machine learning in quantitative prediction of various systems. In January 2020, Kumar published two scientific papers, “Projected distribution and climate refugia of endangered Kashmir musk deer Moschus cupreus in greater Himalaya, South Asia” and “Contrasting responses to climate change at Himalayan treelines revealed by population demographics of two dominant species.” More recently, Kumar co-authored the paper, “A better index for analysis of co-occurrence and similarity.”