- Ph.D., University of Nebraska-Lincoln
- M.Sc., Asian Institute of Technology
- Applied Business Analytics
- Data Storytelling with Visual Analytics
Sharmistha Swain, Ph.D., is an Adjunct Professor of Quantitative Management in the Greehey School of Business at St. Mary’s University. She has more than 12 years of teaching and research experience in statistical computing, location analytics, and satellite image analytics. She has experience in working with large volume of climate, demographic and financial data to develop predictive models for government agencies such as the Environmental Protection Agency, United States Geological Survey, United States Department of Agriculture-Risk Management Agency and several other private organizations in transportation and health care sectors.
In her research and teaching, Swain uses advanced statistical modeling and machine learning algorithms in making optimal decisions pertaining to climate and insurance risk, marketing, finance, health and public opinion related applications. Her research has been published in several high impact factor climate and information systems journals.
Swain earned her Ph.D. in Geographic Information Systems from the University of Nebraska-Lincoln. She has another Ph.D. in Natural Resource Management and an M.Sc. in Regional and Rural Development Planning from the Asian Institute of Technology. She also has a certificate in Business Analytics from the Northwestern University, Evanston, Illinois.
Bradatan, C., Dennis, J., Flores, N., and Swain, S. 2019. Child health, household environment, temperature and rainfall anomalies in Honduras: A socio-climate data linked analysis. Environmental Health, DOI: 10.1186/s12940-020-0560-9.
Griffis-Kyle, K. L., Mougey, K., Vanlandeghem, M., Swain, S., & Drake, J. C. 2018. Comparison of climate vulnerability among desert herpetofauna. Biological Conservation, 225, 164-175.
Swain, S., S. Abeysundara, K. Hayhoe, and A. Stoner. 2017. Future changes in summer MODIS-based enhanced vegetation index for the South-Central United States, Ecological Informatics, 41(64-73), doi:10.1016/j.ecoinf.2017.07.007.
Swain, S. and K. Hayhoe. 2015. CMIP5 projected changes in spring and summer drought and wet conditions over North America, Climate Dynamics, 44 (9-10): 2737-2750.
McIntyre, N. E., C. K. Wright, S. Swain, K. Hayhoe, G. Liu, F. W. Schwartz, and G. M. Henebry. 2014. A Case Study of Macrosystems Ecology: Climate Forcing of Wetland Landscape Connectivity in the Great Plains, Frontiers in Ecology and the Environment, 12(1): 59-64, doi:10.1890/120369.
Swain, S., B. Wardlow, S. Narumalani, D. Rundquist, and M. Hayes. 2013. Relationships between vegetation indices and root zone soil moisture under maize and soybean canopies in the US Corn Belt: a comparative study using a close-range sensing approach, International Journal of Remote Sensing, 34 (8): 2814-2828.
Swain, S., D. Rundquist, T. Arkebauer, S. Narumalani, and B. Wardlow. 2012. Non-invasive estimation of relative water content in soybean leaves using infrared thermography, Israel Journal of Plant Sciences, 60 (2): 25-36.
Swain, S., B. Wardlow, S. Narumalani, T. Tadessse, and K. Callahan. 2011. Assessment of vegetation response to drought in Nebraska using Terra-MODIS Land Surface Temperature and Normalized Difference Vegetation Index. GIScience & Remote Sensing, 48 (3): 432-455.
Swain, S., S. Narumalani, and D. Mishra. 2011. Monitoring invasive species: detecting purple loosestrife and evaluating biocontrol along the Niobrara River, Nebraska. GIScience & Remote Sensing, 48 (2): 225-244.
J.K. Routray and S. Swain. 2004. Participatory land use planning and management of a microwatershed in India, Indian Journal of Regional Science, 36 (1): 73–87.
Swain, S. and J.K. Routray. 2001. Agricultural development planning of Khandamal district of Orissa state in India: a review of current practices and future perspectives, Indian Journal of Regional Science, 33 (2): 32–42.
Swain, S., 2001. Rural urban development strategy for balancing rural-urban relations in India: a brief review, Institute of Town Planners Journal, 19 (1): 43–49.
Wardlow, B.D., T. Tadesse, J. F. Brown, K. Callahan, S. Swain, and E. Hunt, 2012. The Vegetation Drought Response Index (VegDRI): an integration of satellite, climate, and biophysical data. In Remote Sensing of Drought: Innovative Monitoring Approaches, eds. B.D. Wardlow, M.A. Anderson, and J. Verdin, Boca Raton, FL:CRC Press.