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Dr Daphne T. C. Lai Lecturer, Faculty of Science

About Me Publications

Dr Daphne T. C. Lai

Lecturer, Faculty of Science daphne.lai@ubd.edu.bn


ABOUT ME

Daphne Lai is a Computer Science Lecturer at the Faculty of Science, Universiti Brunei Darussalam where she has been a faculty member since 2004.

Her research interests lie in the areas of data mining and artificial intelligence, ranging from applied as well as design. In recent years, she has been investigating on better techniques for cluster analysis and on machine learning applications for predictive analysis. She is collaborating with researchers in several disciplines of health care, particularly cancer registry and cardiac rehabilitation.

She currently serves on the Steering Committee for ASEAN-IVO under NICT and is also a IEEE member.

Daphne is currently lecturing in Programming Fundamentals and Computer Programming.

EDUCATION

BSc in Computer Science, University of Stratchclyde, UK (Thesis: Elliptic Curve Cryptography)
MSc in Distributed systems and Networks, University of Kent, Canterbury, UK. (Thesis: Economy of Stable Job Scheduling in Grid Computing Systems)
PhD in Computer Science, University of Nottingham, UK (Thesis: An Exploration of Improvements to Semi-supervised Fuzzy c-Means Clustering for Real-World Biomedical Data.)

RESEARCH INTERESTS

Data Mining, Artificial Intelligence, Cluster Analysis, Pattern Recognition, Machine Learning, Biomedical Applications, Bioinformatics, Clinical Informatics, Data Science

14

Scopus Publications

51

Google Scholar Citations

4

Google Scholar h-index

2

Google Scholar i10-index


FUTURE PROJECTS

Machine Learning Algorithms

We are studying the following areas of machine learning algorithms: 1) Evolutionary methods for unsupervised/semi-supervised clustering 2) Metric Learning algorithms, similarity measures 3) Model-based techniques 4) Time-based clustering algorithms 5) Intelligent Data Fusion. For interested candidates, please kindly send your research proposals, academic transcripts, and publications, if any.

Application invited for: MSc/ PhD

(Automatic) Data Mining Frameworks

Data mining and machine learning are applied for discovery of patterns and for prediction in the follow domains: 1) Clinical/Biomedical datasets (a) cancer registry, b) health surveys, c) cardiac rehabilitation) 2) Open/public data 3) Driving behaviours 4) Geology For interested candidates, please kindly send your research proposals, academic transcripts, and publications, if any.

Application invited for: MSc/ PhD

Automatic Data Fusion

In this project, we develop a platform or framework that can automate the process of data fusion (integration and feature engineering) of data set from various public sources and data abstraction for knowledge discovery and predictive analysis. For interested candidates, please kindly send your research proposals, academic transcripts, and publications, if any.

Application invited for: MSc


GRANT DETAILS

Grant type: URG, Grant Number: 311, Project Title: Exploring metaheuristics in a semi-supervised fuzzy c-means (ssFCM) clustering framework applied on biomedical data, Investigators (PI/Co-PI): Daphne TC Lai, Funding Details: BND 9,231, Start Date: 01/03/2015, End Date: 29/02/2018


RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)

1. Best Abstract and Best Poster for The Cardiac Society of Brunei Darussalam’s (CSBD) second Annual Scientific Meeting 2015, Brunei for work titled: EVALUATE THE EFFECT OF LONG-TERM COMPREHENSIVE CARDIAC REHABILITATION IN CORONARY ARTERY DISEASE: A COHORT STUDY by authors: SK Jong, DTC Lai, SK Ong and CL Chong.


CONSULTANCY

Consultancy in Data Analytics, Data Mining and Machine Learning is available.
Interested parties may email at daphne.lai[[AT]]ubd.edu.bn
Happy to chat on the application and potential of DM and ML to businesses/industries.

Previous consultancy:
1. PHP 5 for Ministry of Development staff (16 – 18 and 23 – 26 March 2009)
2. FLOSS for local and CLMV (Cambodia-Laos-Myanmar-Vietnam) teachers and system administrators under the Initiative for ASEAN Integration Programme (3 - 5 March 2009)
3. Cascading Style Sheets for Ministry of Development staff (24 - 25 February 2009)
4. Trainer in Linux Software Development (FLOSS training) for Teachers and Ministry of Development staff (June 2007 and March 2008)


Industry, Institute, or Organisation Collaboration

Current Projects
1) Cluster Analysis of Cancer Registry with Ministry of Health (Aug 2014 - present)
2) Semi-supervised hierarchical clustering (Feb 2016 - present)
3) Metaheuristics in semi-supervised Fuzzy c-means (Mar 2015-present)
4) Applying Machine Learning techniques on National Health Survey data (Aug 2017 - present)
5) Applying Machine Learning techniques to study driving behaviours collected from simulation (Aug 2017 - present)

Past Project:
1) 2) Evaluate Effects of Cardiac Rehab Programme with MOH (Jun 2014 - Sept 2017)
2) Semi-supervised Fuzzy c-Means clustering methodologies for Real-World Biomedical Data with University of Nottingham (Oct 2010 - May 2014)


SOCIAL, ECONOMIC, or ACADEMIC BENEFITS

Patterns that are not easily determined (due to high number of parameters and records) can be found using data mining techniques, allowing the prediction of outcomes on new data records. Applied in the biomedical field, this enhances the understanding of the disease and its outcome through characterisation of these patterns based on the parameters.

Data Mining and Machine Learning has been widely applied in the field of medicine, agriculture, education, logistics, ecology, retail and so forth. By learning from data, we can find hidden patterns and create useful models to be used for prediction. This has provided decision-support or additional insights to domain experts.


Scopus Publications