Fei Li

Office: 4945 BBBB, 2260 Hayward Street
Ann Arbor, MI, 48109-2121
Department of Electrical Engineering and Computer Science
University of Michigan
Email: lifei AT umich DOT edu


About Me:

I'm a Ph.D. candidate advised by Professor H. V. Jagadish at the Database Group, University of Michigan. My research interests focus on Database Usability, especially, how to enable non-technical users to compose logically complex queries. Before that, I worked on Data Integretion in Harbin Institute of Technology when I was an undergraduate student.

Besides, I am the cofounder of Caimi, which helps non-technical users query Chinese stock market data. It already accumulated more than 100,000 registered users.


Projects:

NaLIR is a generic interactive natural language interface for querying relational databases. It is able to handle even quite complex queries in a variety of application domains, and the carefully designed interactive communications can avoid misinterpretation with minimum user burden.

Schema-free SQL is a framework that enables users to specify queries over relational databases without requiring full knowledge of the schema. Schema-free SQL respects whatever specifications are given, all the way from a little more than keywords to full SQL.

Approximate XML Joins (undergraduate): Various approaches are proposed to enhance the efficiency and accuracy in approximate XML joins, e.g. hash-based methods, transformation-based methods and filter-refinement mechanisms.

Publications:

Constructing an Interactive Natural Language Interface for Relational Databases.
F. Li and H. V. Jagadish
VLDB, 2015 (Best Paper Award).

Schema-Free SQL.
F. Li, T. Pan, and H. V. Jagadish
SIGMOD, 2014.

NaLIR: An Interactive Natural Language Interface for Querying Relational Databases.
F. Li and H. V. Jagadish
SIGMOD (demo), 2014.

Approximate XML Joins at Label Level.
F. Li, H. Wang, L. Hao, J. Li and H. Gao
Information Science, 2014.

A Survey on Tree Edit Distance Lower Bound Estimation Techniques for Similarity Join on XML Data.
F. Li, H. Wang, J. Li and H. Gao
SIGMOD Record, 2013.

Usability, Databases, and HCI.
F. Li and H. V. Jagadish
IEEE Data Eng. Bull, 2012.

Efficient Algorithms for Identification of Similarity XML Fragments based on Tree Edit Distance.
H. Wang, J. Li and F. Li
XML Data Mining: Models, Methods, and Applications, Andrea Tagarelli, 2012.

Approximate XML Joins Using g-String.
F. Li, H. Wang, C. Zhang, L. Hao, J. Li and H. Gao
VLDB workshop - XSym, 2010.

pq-Hash: An Efficient Method for Approximate XML Joins.
F. Li, H. Wang, L. Hao, J. Li and H. Gao
WAIM workshop - XMLDM, 2010.