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Bolin Ding

Bolin Ding

Contact Information

Microsoft Corporation
One Microsoft Way
Redmond, WA 98052
Tel: +1 (425) 704-9176

I am a Researcher in the Data Management, Exploration and Mining (DMX) group at Microsoft Research. Before joining Microsoft, I completed my Ph.D. in Computer Science at University of Illinois at Urbana-Champaign under the supervision of Prof. Jiawei Han.

Research Interests

My research goals and interests span different aspects of large-scale data management, including search and explore structured data, database systems, data mining algorithms and applications, and data privacy. I'm particularly interested in (randomized or approximation) algorithms which have performance guarantees in theory, and are effective and robust in practice as well.

  • Search structured data: inventing new search models / interfaces to help people explore structured (text) data more easily, and developing efficient algorithms and index structures to support them
  • Query processing: i) faster algorithms for building block components, and ii) progress estimation in query processing
  • Data mining: developing data mining algorithms for various applications
  • Data privacy: reducing the amount of noise while providing (mathematically) rigours and flexible privacy guarantees
  • Graphs in databases

Selected Publications

Search Structured Data: Models and Algorithms
Query Processing
Data Mining: Algorithms and Applications
Data Privacy
Graphs (in Databases)

Professional Activities

Program Committee Memberships:

  • The 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2014)
  • The 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2013)
  • The 1st International Workshop on Privacy-Preserving Data Publication and Analysis (PrivDB 2013), in conjunction with the 29th IEEE International Conference on Data Engineering (ICDE 2013)

Reviewer for Journals:

ACM Transactions on Database Systems, IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Knowledge Discovery from Data, Theoretical Computer Science, Pattern Recognition, Information Sciences, Knowledge and Information Systems