Discovery Park Undergraduate Research Internship Program

"Modeling of Precipitation and Droughts"

About the Project

Project Time & Type:
Summer 2013 - DURI
Research area(s):
Machine Learning, Hydrology
Project Description:
Drought is a prolonged shortage of water, and its effects are felt in many areas of human activity, with agriculture as a primary example. We are developing statistical tools that can evaluate and potentially simulate droughts based on the historical data.
Expected Student Contributions:
The student will learn about the techniques used to model multivariate time series data (in the hydrological setting), and will contribute to many stages of the project including data selection, organization, and cleaning, data visualization, implementation of the models, set-up of the experiments, and analysis of the results.
Related Website(s):
Desired Qualifications:
Required: strong programming skills (experience with C/C++, Matlab, R, or Python), strong mathematical skills (full sequence of lower division calculus), a course in machine learning/artificial intelligence; strongly desired: some background in probability and statistics.
Estimated Weekly Hours:
Department awards independent research credits for this project?

Professor in Charge

Kirshner, Sergey

Student Supervisor

Sergey Kirshner
Assistant Professor, Statistics

Cooperating Faculty

Rao S. Govindaraju
Civil Engineering