Research Interests

My research interests lie in human-computer interaction. I am particularly interested in information visualization and socially relevant technologies. By socially relevant I mean that I am interested in helping design technologies that make the world a better place with respect to education, environmental sustainability and economical opportunities for the low-income communities in the developing world.

Projects

2006-		CAM Automating Paper-based processes using a Camera-equipped Mobile Phone. Sustainable rural technology research in the developing world.
2004-06		Indicator Browser: UrbanSim results visualizer The Indicator Browser is a web-based interface that allows users to request and retrieve UrbanSim's simulation results visualizations. This project is part of an effort to create a user-centered interface for UrbanSim. UrbanSim is a large scale land use and transportation simulator that models the possible long-term effects that adopting urban policies can have on the region. UrbanSim is being developed in order to aid in the democratization of the urban planning process by allowing both experts and engaged citizens to make more informed decisions regarding land use and transportation policies.
2002-04		High Performance Computing Job Scheduling BlueView: Visualization of supercomputer job reservations BlueView is a tool that visualizes Blue Horizon, IBM's supercomputer, job reservations in order to help users make an informed decision on their job configuration, maximizing node utilization and per-SU performance. Are User Runtime Estimates Inherently Inaccurate? Computer system batch schedulers typically require information from the user upon job submission, including a runtime estimate. Inaccuracy of these runtime estimates, relative to the actual runtime of the job, has been well documented and is a perennial problem mentioned in the job scheduling literature. This study examines user behavior when the threat of job killing is removed, and when a tangible reward is provided for accuracy. We show that under these conditions, about half of users provide an improved estimate, but there is not a substantial improvement in the overall average accuracy.