I am honored to have been selected to receive a 2012 National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) Fellowship. This will cover 3 years of my PhD program.

,I have been heavily involved in the environmental research community, focusing on environmental sensor networks. These networks collect meteorological, terrestrial, and hydrological data for the study of the environment on a wider temporal and spatial scale than traditional manual sampling would allow. Traditional techniques involve going out into the field periodically to manually collect data. This technique produces sparse data point often weeks or even months apart.

In contrast, sensor networks allow continuous data collection and are often deployed in habitats that are difficult to access. The data they gather translates into ecological knowledge that was previously unattainable.

The capacity for continuous monitoring comes at a cost. These networks generate magnitudes more data than traditional techniques, often taking hundreds of readings per hour and using high bandwidth sensors such as video. Shifting through all the data manually to find points of interests is often impossible, as certain data formats, like images, require inspection of each individual image. To process this quantity of data, sensor networks need cyber-infrastructure that is scalable, extendable, and reliable to support them.

Computer scientists seek to develop toolkits and algorithms for the automated analysis and event detection of numerical and image data for points of interest. Although this is still a developing field, scientists are beginning to use automated algorithms to do studies never before possible.

In my degree I will look at systems and algorithms for improving environmental monitoring approaches.