Assistant Professor of Clinical, Departmet of Data Science and Operations, Marshal School of Business
I am an applied statistician specializing in time series analysis, machine learning, wavelet techniques, functional data analysis, and applications to finance, business analytics, economics, hydrology, remote sensing, precision agriculture, and climate change problems.
At my current job at Marshall School of Business, USC I have been teaching and developing courses in machine learning, business statistics, data analytics and visualization.
I also worked at
- provided subject matter expertise and guidance to the Data Science Community;
- acted as the senior consultant advisor during executive meetings for Data Science-aligned Corporate and Operations Architecture Strategic Priorities;
The World Bank:
- used machine learning models to forecast commodity prices;
- studied business cycle synchronization within East African Union and provided recommendations for a currency union;
Utah Water Research Lab
- lead a team of graduate students and post-docs in developing and implementing machine learning models for precision agriculture;
- analyzed drone data to help farmers make better crop management decisions;
American University, Washington DC
- developed methodologies that detect the changes in the Pacific sea surface temperature, snowpack and their effects on the streamflow using the wavelet-based techniques combined with multivariate Bayesian machine learning models.
- taught and developed undergraduate and graduate courses in statistical learning, business statistics, applied regression, multivariate analysis, time series, data analytics, and visualization
I received my BS in Mathematical Statistics from Vilnius University, Lithuania; MS and PhD in Statistics from Utah State University.