Research
My principal research interest is in large-scale information and social networks, and more generally in data mining, database systems,
statistics, machine learning, information retrieval, and network
science, with a focus on modeling novel problems and proposing scalable algorithms
for large-scale, real-world applications, including but not limited to:
social computing, social media, business intelligence, medical and
health informatics, and cyber-physical systems.
In particular, I have extended conventional studies of
homogeneous
networks to modeling typed nodes and links in semi-structured
heterogeneous information networks and proposed new models and
algorithms that capture the rich semantics of multi-typed objects and
links in such networks and solve real-world problems. My research has been
focused on new methodologies of mining such networks and exploring the
power of typed objects and links.
My recent research focuses on mining heterogeneous information networks with social factors, i.e., networks with human involved. We are exploring data from different domains, such as online social networks, online discussion boards, digital government, and game data.
Selected Projects
- Latent Social Characteristics Learning
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Recommendation via Information Networks
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Co-Evolution Detection and Link/Relationship
Prediction in Dynamic Heterogeneous Information Networks
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