Research

Demand response is an area that focuses on enabling electricity customers manage their consumption during peak demand periods. There are different strategies such as variable pricing and other incentives that are being investigated to realize load curtailment. The rapid growth in demand for energy is beginning to strain the current infrastructure, potentially threatening the stability of electric grids. In this project, we are looking at different optimization techniques to manage and regulate consumption. Our research focuses in the areas of semantic Web, Integration and analysis of high throughput data, large scale and distributed computing, and social computing. As an emerging yet critical area of research, this project offers excellent scope for innovation and research for research faculty and graduate students.

The collaborators in this effort include the Los Angeles Department of Water and Power and USC Facilities Management, and the work is sponsored by the Department of Energy as part of the Los Angeles Smart Grid Demonstration project.

IAM is a fast-paced research project that seeks to apply core computer science concepts to challenging problems in the oilfield domain. Specifically, our objective is a creative synthesis of ideas from a wide variety of domains including software architecture, distributed and grid computing, artificial intelligence, semantic web, data integration, and services computing, in an attempt to create a knowledge management and workflow management layer for oilfield applications. The project offers a host of challenging opportunities for motivated graduate students. The IAM project is part of the joint USC-Chevron CiSoft effort to realize the vision of an integrated, instrumented, intelligent oilfield. The project team includes computer scientists from USC, domain experts from Chevron, and technology advisors from Microsoft and Avanade.