My research focuses on artificial intelligence, machine learning and data mining, with applications in bioinformatics and computational biology. My work explores graph-based learning, knowledge discovery and predictive modelling for complex biological systems. Current research interests include graph neural networks, explainable AI, protein and biological network analysis, and AI-driven biomedical discovery.

NTU DR publications/profile

https://dr.ntu.edu.sg/entities/person/Kwoh-Chee-Keong

https://dr.ntu.edu.sg/entities/person/Kwoh-Chee-Keong/full

PUBLICATIONS

Google Scholar

https://scholar.google.com.sg/citations?hl=en&user=jVn0wDMAAAAJ&view_op=list_works&sortby=pubdate

ResearchGate

https://www.researchgate.net/profile/Chee-Keong-Kwoh

ORCID

https://orcid.org/0000-0002-8547-6387

dblp

https://dblp.org/pid/32/228.html

https://research.com/u/chee-keong-kwoh

MY GRANTS

· Host-pathogen protein-protein interaction approaches for predicting virulence

· The discovery of neutralizing antibodies for potential novel coronavirus through machine learning approaches

· Explainable AI for Multimodal Predictive Maintenance of Jet Engines with Smart HCI

· Hybrid Finite Element Method And Mixedlevel Coarse GrainingMolecular Dynamics Simulation

· Computational Virulence Model With Functional Information For Influenza Viruses

· Structural analysis and characterization of protein complexes

· Towards direct and rapid mapping of RNA modifications with nanopore sequencing

· Untangling cancer re-wiring: Pan-Cancer mapping of transcription factor driven dysregulatory hotspots using AlphaFold2 and integrative machine learning

· Investigating the regulation of 3D genome organization using machine learning

· Predict the solubility of proteins using machine learning

· Hodge Laplacian based deep learning models for drug design

· Challenge-Learn: Developing and Assessing an Andragogical Programme and System based on Co-Skilling to Enhance Employability and Learning

· Artificial intelligence for the prediction of alternative splicing from epigenomics and transcriptomics data in cancer

· Computational Systems Biology of Synthetic Lethality Towards New Cancer Medicine

· Predict the solubility of proteins using machine learning

· AI Enhanced Creativity In Education

· Computational Systems Biology of Synthetic Lethality towards New Cancer Medicine

· CloudDock: Molecular Docking Platform on Cloud

· Methodological Investigation for Automatic Detection of Primary Angle Closure Condition (PAC) and PAC induced Glaucoma

· Bioinformatics Algorithms for Detecting Genetic and Epigenetic Determinants of Meiotic Recombination Hotspots from Genomic Data

· Core-Attachment based Mining Technique: to detect Protein Complexes and Protein-Small Molecule Interactions

· Core-Attachment based Mining for Protein Complexes & Small-molecule Interactions

· Improved Design via Evoltionary Algorithms

· The Protein Binding Hot Spots Are Water Free?

· Neural Systems Modeling with functional MRI

· Function MR Time-Series Analysis

· Augmented reality for prosthesis cup placement

· Cardiovascular & respiratory systems' signal simulation, processing and analysis for ICU, or and telemedicine applications.Computational Virulence Model with Functional Information for Influenza Viruses

· Protein binding hotspots are water-free?

· Analysis of Past DRG data for the study of LOS for better utilization of Hospital Resources

· Data Warehousing and Data Mining Analysis of Staphylococcus Aureus

· A novel approach for inter- to intra- network analysis of genetic diseases using high-throughput data

· Neural Systems modelling with functional MRI

· SCE incubator proposal for “Evolutionary and Complex Systems Lab”

· The Application of ultrasound-based augmented reality with the directional vacuum-assisted breast biopsy device in the treatment of breast cancer

· Distributed Diagnosis and Home Healthcare (D2H2)

· Development of a robotic semi-automated remote handling system for radioiodine dispensing

· Functional MR Time-Series Analysis

· Augmented Reality for Prosthesis Cup Placement

· Robotic Skull Based Surgery

· Cardiovascular and Respiratory Systems' Signal Simulation, Processing and Analysis for ICU, OR and Telemedicine Applications.

· Strategic research: Interventive augmented reality for medical applications.

· Surgeon Assistant Robot for a Selected urological disorder.

MY GRADUATE STUDENTS

· Lin Dehui

· Wang Jing

· Ng Zu Wei Jovin

· Lyu Kuangda

· Pang Xihern

· Tjio Ci'en Gabriel

· Tan Lai Heng - Using Machine Learning to improve Nucleic Acid-Ligand Binding Prediction (PhD, 2026)

· Hou Yubo - Overcoming Domain Shift in Time Series Data for Remaining Useful Life Prediction: From General to Incomplete Degradation (PhD, 2026)

· Emadeldeen Ahmed Ibrahim Ahmed Eldele - Towards Robust and
Label-efficient Time Series Representation Learning (PhD, 2023)

· Zhang Yu - Long Non-coding RNA Functional Annotation: Machine Learning Approaches (PhD, 2022)

· Mohamed Ragab Mohamed Adam - Towards Practical Data-Driven Predictive Maintenance: A Robust and Generalizable Deep Learning Approach (PhD, 2022)

· Lin Zhuoyi - User-Specific Recommender Systems: From Data to Model (PhD, 2022)

· Li Xinya - Predictive Modeling of Genome Regulation: Chromatin Interaction Prediction From Small-Scale Hi-C and Virtual Cell Perturbation Response Modeling (PhD, 2025)

· Yin Rui - Meta-analysis on the lethality of influenza A viruses using machine learning approaches (PhD, 2020)

· Zhou Xinrui - Computational virulence model with functional information for influenza viruses (PhD, 2019)

· Ata Kircali Sezin - Learning graph representations for disease gene prediction (PhD, 2019)

· Amr Ali Mokhtar Alhossary - Accurately Accelerating Drug Design Workflow (PhD, 2019)

· Aly Mohamed Alaaeldin Aly Ezzat - Aly Mohamed Alaaeldin Aly Ezzat (PhD, 2016)

· Pradhan Mohan Rajan - Biomolecular hydration in protein-protein interaction, protein stability and aggregation, and lead optimization: computational studies (PhD, 2016)

· Pan Hong – DNA methylation biomarkers of personal disease risk (PhD, 2016)

· Luay Aswad - A molecular basis of the 5-gene breast tumour aggressiveness grading signature (AGS) and its network – PhD, (2016)

· Han Xu - Constructing the Semantic Web for Biomedical Literature (PhD, 2015)

· Ouyang Xuchang - Automated and Accelerated Covalent Docking and Covalent Virtual Screening (PhD, 2010–)

· Thidathip Wongsurawat - Computational Analysis and Prediction of Specific Genomic Regions Forming R-loop Structure and Chromosomal Variations Associated with Cancer (PhD, 2015)

· Zhang Zhou - Knowledge Discovery In Post Genome-Wide Association Study For Glaucoma (PhD, 2015)

· Su Tran To Chinh - Improving the Discrimination of Near-Native Complexes for Protein Rigid Docking by Implementing Interfacial Water into Protein Interfaces (PhD, 2015)

· Yang Peng - Computational Approaches for Disease Gene Identification (PhD, 2014)

· Wu Min - Mining Protein Complexes From Protein Interaction Data (PhD, 2012)

· Zhang Tianyou - Contact Network Based Framework For Infectious Disease Interventions (PhD, 2015)

· Stephanus Daniel Handoko - Constrained-Oriented Refinement-Efficacious Memetic Algorithms for Efficient Optimization of Computationally-Expensive Problems (PhD, 2014)

· Adrianto Wirawan - Whole-Genome Discovery Of Transcriptional Regulator Binding Sites (PhD, 2011)

· Zhang Guanglan- Computational Epitope-Driven Vaccine Design (PhD, 2008)

· Zheng Yun- Design Of Gene Expression Networks From Microarray Data (PhD, 2006)

· Zhao Ying- Efficient Model And Feature Selection For SVM In Biomedical Data Analysis (M Eng, -2004)

· Zhao Jianhui- Human Animation from Motion Recognition, Analysis and Optimisation ( PhD, 2003)

· Chen Yintao - Image Processing For Ultrasound Guidance System In Breast Lump Operation (M Eng, 2002)

· Wang Yan - Image-Based Indexing And Retrieval Of Trademark Logos, (M Eng, 2001)

· Veena Mohan Bhajammanavar - Image Processing Of The Digital Mammogram For Segmentation And Characterization Of Microcalcifications, (M Eng, 2000)

· Misra Sabita - Time Series Analysis Of ECG For Detection Of Premature Ventricular Contraction (M Eng, 2000)

· Zou Qingsong - Object-Based Volume Visualisation For Medical Imaging (PhD, 2001)

TEACHING

Planned and lectured subjects in

CZ4032 Data Analytics and Mining (2014,15): Data Mining is an analytic process designed to explore big data in search of consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the algorithms to new data.
CE7411 Bioinformatics (2015): This course covers basic bioinformatics concepts, databases, tools and applications. Introduction: cell biology's central dogma, biological technologies for collecting and storing genomic sequence data; databases that store these data and strategies to extract information from them; Pairwise sequence alignment for assessment of similarity to infer homology; Fundamental of Scoring matrices to understand the assigned scores when performing alignment; The popular heuristic search tool - Basic Local Alignment Search Tool (BLAST) and advanced database searching; Multiple sequence alignment and phylogenetic trees to complete the coverage from genomic sequences. Functional genomics with the introduction to gene expression. Processes for microarray data analysis; Feature selection and classification for microarray data analysis. Protein families & proteomics; Protein structure and structural genomics; and Molecular evolution and phylogeny.
BI6123 Methods and Tools of Proteomics (2007): Proteomics study and identify protein structure, interactions of protein/protein and protein/DNA and biology of organisms. We will further introduce the newly developed technology for the quantitative analysis of protein expression and function on a genome-wide scale.
BI1602 and SC448 Introductory Bioinformatics (2005,06): Basic bioinformatics concepts. Databases, tools and applications.
BI1603 Computational Biology (2006) Introduce the applications of the techniques of computer science, applied mathematics, and statistics to address problems inspired by biology. Major computational techniques used in biology include Bayes, HMM, MI etc.
BG3011 Biocomputing (2005, 06): Introduction the new course of biocomputing for students in SCBE, the subject is first offered in July 2005; It covers Concepts; Bioinformatics databases; Sequence alignment; Phylogeny and protein structure prediction.
BI6104 Biostatistics: First offered in July 2003, this course equipped the students in MSc with Knowledge of statistics, experimental design and statistical learning.
Curriculum for MSc in Bioinformatics: From August 2001 to June 2002, I worked with Vice-Dean (Academic) SCE, Head, Natural Science of NIE, Vice-Dean (Academic) of SBS and Professor from MPE and EEE to structure the new MSc in Bioinformatics.
SC104 Mathematics I Fundamental of mathematics for Engineering include statistics and calculus
CE307 Computer Peripherals: In 1996-2000, re-design the course to include start-of-the-art techniques such as PRML, USB and Bluetooth.
M495 & M6524 Medical Assist Surgery (2000-2002): Co-planed and lectured the final year and MSc elective for Biomedical Engineering.
Digital Signal Processing (1992): Planed and lectured the final year elective for the computer engineering.

MY PHD THESIS

GRADUATE ADVISORS: Prof Duncan Fyfe Gillies - Professor of Biomedical Data Analysis, Department of Computing, Imperial College London

My PhD thesis Probabilistic Reasoning From Correlated Objective Data, University of London, Imperial College