Daphne T. C. Lai


Lecturer, Faculty of Science and Researcher, Institute of Applied Data Analytics



Daphne Lai is a Computer Science Lecturer at the Faculty of Science, Universiti Brunei Darussalam. 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, Computer Programming and Data Mining.

For postgraduates
There are vacancies for interested Masters & PhD candidates with numerous proposed projects listed below, please kindly email your research proposals, academic transcripts, and publications.
Scholarship application websites:


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.)


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


Machine Learning and/or Data Mining

We study and investigate in following 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) Computer Vision algorithms With applications into 1) Clinical/Medical Data 2) Geology 3) Material Science 4) Biology etc

Applications Invited
MSc or PhD Level

Modelling and Identifying Driving Patterns of Brunei Drivers.

The main aim of this research project is to study the driving patterns of drivers in Brunei using simulation and sensor data and machine learning techniques, identifying extensively detailed driving parameters thereby helping drivers to improve road safety.

Applications Invited
PhD Level

Integrating microscale chemistry experiments with mobile app

The main objective of this study is to develop a new and alternative manner of conducting experiments in a chemistry laboratory that are significantly lower in cost, environmentally-friendly, easy to use and with improved effectiveness as a learning tool in studying chemistry.

Applications Invited
MSc Level

Scopus Publications


Google Scholar Citations


Google Scholar h-index


Google Scholar i10-index

Scopus Publications


Grant Number: URG 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


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 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) Data Analytics 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)
6) Applying ML techniques to studying source rock characterisation and TOC prediction (Sep 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)


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 a specific domain, e.g in the biomedical field, this can enhance the understanding of the disease and its outcome through characterisation of these patterns based on given 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.