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Colloquium - Lv

Towards Efficient and Effective Data Management and Exploration in the Digital Era
Department of Computer Science
9/16/2010
3:30pm-4:30pm

We are quickly moving into a digital era in which huge amounts of digital data are continuously generated yet human's capabilities are very limited in terms of "digesting" such massive data for information exploration and knowledge discovery. This calls for a paradigm that goes beyond traditional storage and retrieval of raw data blocks and aims to "make sense" of data at a large scale. Through the integration of efficient system design and effective data analysis techniques, our goal is to discover and exploit useful patterns from large amounts of data with high quality and high efficiency.

This talk gives an overview of my research on massive data management and exploration, which bridges the areas of search systems, data mining, mobile systems, social networks, and data management. I will present the two specific themes of my research. For data-oriented mobile social computing, I have investigated distributed mobile data management, social data analysis and recommendation, and social networking in rural communities. For data-oriented scientific discovery, working with domain experts, my research centers around data management and data analysis in environmental sensing of air pollutants, time-series analysis of cryospheric data, and energy storage system design for transportation electrification.

Qin (Christine) Lv is an assistant professor in the Department of Computer Science, University of Colorado Boulder. She received a BE with honors from the Department of Computer Science and Technology, Tsinghua University in 2000, and a PhD from the Department of Computer Science, Princeton University in 2006. Before joining the University of Colorado, she also spent one year in Princeton University as a postdoc, and one year in the Computer Science Department, Stony Brook University as an assistant professor.

Lv's primary research interest is massive data management and exploration. Her research integrates efficient systems design with effective data analysis techniques. Her research focuses on search systems, data mining, mobile systems, social networks, and data management. Lv's research is interdisciplinary in nature and interacts closely with a variety of research domains including environmental research, geophysics, renewable and sustainable energy, as well as the information needs in people's daily lives.

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