Qin (Christine) Lv
Assistant Professor, University of Colorado Boulder
Thursday, July 18, 2013
Big data is becoming the norm in a wide range of application domains, be it science, engineering, education, commerce, national security, or people's daily information needs. Typically characterized by the 4Vs (volume, velocity, variety, and veracity), big data is continuously generated yet human's capabilities are very limited in terms of digesting such massive and complex data for information exploration and knowledge discovery. This calls for a paradigm shift that goes beyond traditional storage and retrieval of raw data and aims to make sense of data at scale. Through the integration of efficient system design and effective data analysis techniques, along with domain specific knowledge, our goal is to discover and exploit useful patterns in big data with high quality and high efficiency.
This talk gives an overview of my research on big data analytics, which bridges the areas of ubiquitous computing, data mining, mobile systems, social networks, and data management. Two specific themes of my research will be presented. For data‐oriented scientific discovery, working with domain experts, my research centers on 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. For data oriented mobile social computing, I have investigated distributed mobile data management, social data analysis and recommendation, and video chat in online and mobile settings.
Qin Lv is an Assistant Professor in the Department of Computer Science, University of Colorado Boulder. She received her Ph.D. in Computer Science from Princeton University in 2006. Before joining CU, she also spent one year in Princeton University as a postdoc, and one year in the Computer Science Department of Stony Brook University as an Assistant Professor.
Lv's research integrates efficient system design and effective data analysis for the management and exploration of big data. Her research spans the areas of ubiquitous computing, data mining, mobile systems, social networks, and data management. Her research is interdisciplinary in nature and interacts closely with a variety of research domains including environmental science, geosciences, renewable and sustainable energy, materials science, as well as the information needs in people's daily lives. Lv has over 40 peer-¬‐reviewed publications in many top venues including UbiComp, MobiSys, Pervasive, WWW, KDD, SIGMETRICS, etc. She has one Best Paper Award nomination, and her work on personalized driving behavior monitoring and analysis for emerging hybrid vehicles won the Computational Sustainability Award bestowed jointly by the Computing Community Consortium (CCC) and Pervasive 2012.
Hosted by Richard Han.