Lee Mong Li is an Associate Professor and Assistant Dean
(Undergraduate Studies) in the School of Computing at the
National University of Singapore.
She received her Ph.D., M.Sc. and B.Sc. (Hons 1) degrees in Computer
Science from the National University of Singapore in 1999, 1992 and 1989
respectively. Her Ph.D. thesis examines translation, integration and update
issues in a federated database environment.
She was awarded the IEEE Singapore Information Technology
Gold Medal for being the top student in the Computer Science program
in 1989.
Mong Li joined the Department of Computer Science, National University
of Singapore, as a Senior Tutor in April 1989 and
was appointed Fellow in the School of Computing in February 1999.
She was a visiting Fellow at the Computer Science Department, University of Wisconsin-Madison, from September 1999 to August 2000 and Consultant at
Quiq Incorporated, USA from June to August 2000.
Her research interests include the cleaning and integration of
heterogeneous and semi-structured data, database performance issues in
dynamic environments, and medical informatics. Her work has been
published in database conferences such as ACM SIGMOD, VLDB, ICDE and
EDBT,
data mining conference ACM SIGKDD and database conceptual
modeling conference (ER).
Research
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Publications
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Projects
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RetinaMiner: Mining Changes in Retinal Images
This project is funded by ASTAR SERC.
The vascular structure of a retina image has been shown to reflect the
cardio-vascular states of the human body. Careful study of the changes
in retina images can enable clinicians to monitor, predict, and manage
diseases at an early stage.
This project aims to develop methods to precisely extract
and tracks vascular structures from digital retinal images
to compute vessel caliber, branch angles and tortuosity.
Retinal images over multiple time points are registered to detect changes.
These data are tagged using XML for subsequently querying of changes.
Techniques to discover spatio-temporal patterns
that highlight the interesting changes that occur in these vascular
structures are developed.
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SiRIAN: Singapore Retinal Imaging and Archival Network
The SiRIAN programme, funded by ASTAR SBIC, is
focused on the development and evaluation of
computer-based, automatic retinal vascular imaging system for risk
prediction. We will leverage on the linkage of retinal image features
with demographic and clinical data for a comprehensive
approach. This project involves collaboration between Centre of Eye Research
Australia (CERA), I2R and NUS School of Computing.
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RETINA: a RETinal INformation Analysis system
This is an NUS-NSTB funded project. The objective of the project
is to employ a combination of innovative image processing
and mining techniques to automate the preliminary
analysis and screening of specific diabetic and age-related eye diseases from
digitized retinal photographs of diabetic patients. This project is a
joint collaboration between National Healthcare Group Polyclinics,
Tan Tock Seng Hospital and NUS School of Computing.
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Knowledge Discovery in Biological and Clinical Data
This is an I2R-SoC joint research project funded by ASTAR. The project
aims to construct a knowledge discovery and data mining platform
for biological and clinical researchers to extract new knowledge and
value-added information from diverse data sets.
In particular, we have
developed a taxonomy of artifacts observed in molecular databases,
methods that recognize micro RNA precursors from genomic sequences,
and techniques to discover network motifs and increase the reliability of
interactions in protein-protein interaction networks.
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InteliClean: a Knowledge-Based Framework
for Intelligient Data Cleaning
This project integrates de-duplicating strategies and methods
into a general purpose and complete data cleaning system.
The objective is to obtain a set of higher quality data for mining and
warehousing.
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Next Generation Electronic Business Hubs
Supported by the NUS Academic Research Fund, this project aims
to design an Electronic Business Hub
(EBH) to provide business partners, government services, and
customers with a portal, or an interactive "window," into their
collaborative business environment. The hub will be able to integrate front
and back office applications, supply chain and e-business capabilities.
Users will be able to seamlessly access internal and external applications,
hosted services and business content via a single, easy-to-use
Web-based environment.
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Professional Activities
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Graduate Students
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Resources
Teaching
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