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Research

  • Big Picture

    My general interests are data mining and big data analytics, especially (1) how analytical approaches alleviate information overload, heterogeneity, and asymmetry and (2) what role modeling regulations play in exploring the correlations among big data.

  • Recent Focuses

    My research intersects spatiotemporal textual mining, probabilistic modeling, and heterogeneous information fusion. I aim to understand the fundamental limits of what can be learned from heterogeneous data, and to design practical algorithms and tools that approach these limits. My recent research focuses on collective learning while providing reliability, efficiency, fairness and privacy guarantees. I also investigate how the developed algorithms and tools can be applied for big data problems, including urban computing, human mobility modeling, wireless intelligence, recommender systems, consumer analytics, and health care.

Selected Projects