Speakers
Keynote
Dr. Poo Kuan Hoong
Google Developer Expert (GDE), AWS Community Builder, Senior Manager Data Science, Consultant, Trainer, Podcaster, Founder Malaysia R User Group, AI & ML Malaysia User Group
THE R EVOLUTION: HARNESSING GENERATIVE AI FOR NEXT-GENERATION DATA SCIENCE
With 15 years of academic and research experience, Dr Poo is a passionate practitioner in the area of Data Science, Machine Learning and Artificial Intelligence. A graduate of Nagoya Institute of Technology (Japan), Dr. Poo holds a Doctorate degree (Ph.D.) in Computer Science, a Master of Information Technology (UKM), and a Bachelor of Science (UKM). He is currently working as Lead Data Scientist where he applies his combination of research and industrial experience in Big Data Analytics, Data Mining, Machine Learning and Artificial Intelligence to provide innovative solutions. Besides that, Dr Poo founded two communities in Malaysia: Malaysia R User Group and TensorFlow & Deep Learning Malaysia User Group.
Prof. Ts. Dr. Lau Sian Lun
Deputy Dean of Engagement and Internationalisation and Head of Department for the Department of Computing and Information System, School of Engineering and Technology, Sunway University
R, PYTHON & LATEX
Prof. Lau Sian Lun received both his MSc and Dr.-Ing. at the University of Kassel, Germany, where he worked as a full-time researcher from 2004. He has contributed and managed various German national as well as EU-funded projects, such as the EU FP6 MobiLife, ITEA S4ALL, BMBF MATRIX and the EU FP7 SEAM4US schemes. He has a distinguished publishing record, having authored over 50 publications for conferences, workshops, book chapters and journals such as World Applied Sciences Journal, IEEE Vehicular Technology Magazine, Jurnal Teknologi and more. He is currently a senior member of the Institute of Electrical and Electronics Engineers (IEEE). His research interests focus on areas of ubiquitous computing, sustainable smart cities, context-awareness and applied machine learning.
Dr. Wan Nor Arifin Bin Wan Mansor
Senior Lecturer In The Biostatistics And Research Methodology Unit, School Of Medical Sciences, Universiti Sains Malaysia
PUBLICATION-READY STATISTICAL RESULTS USING R
Dr. Wan Nor Arifin bin Wan Mansor is a Senior Lecturer in the Biostatistics and Research Methodology Unit at the School of Medical Sciences, Universiti Sains Malaysia (USM). He holds an MBBS from Universiti Islam Antarabangsa Malaysia, an MSc in Medical Statistics from USM, and a PhD in Intelligent Systems from USM, Kubang Kerian. Dr. Wan Nor Arifin specializes in medical statistics and research methodology, particularly using the R programming language, which he promotes in medical research. His research interests include developing and validating measurement tools in clinical and public health settings, machine learning applications, sample size calculation, and statistical methods. He is actively involved in creating R functions and packages, enhancing computational algorithms, and teaching statistical programming. Dr. Wan Nor Arifin is recognized for his contributions to statistical methodology and the integration of machine learning in health research, making him a key figure in advancing medical research methodologies.
This talk provides an overview of creating publication-ready statistical results in R for academic articles and theses. It covers customizing tables and plots, and effectively embedding results in text from raw R outputs. Examples based on R packages and advanced customization are demonstrated.
Assoc. Prof. Dr. Wan Fairos Wan Yaacob
Associate Professor at Universiti Teknologi MARA
SAMPLING-BASED APPROACHES FOR HANDLING CLASS IMBALANCE IN MACHINE LEARNING CLASSIFIER WITH R
Dr. Wan Fairos Wan Yaacob is an Associate Professor at Universiti Teknologi MARA, Kelantan, and Head of the Business Datalytics Research Group. She holds a PhD in Statistics and specializes in statistical modeling and data mining, with a focus on panel count models for road accidents and Monte Carlo simulations. Her research interests include traffic accident modeling and dengue disease modeling, using hierarchical Bayesian methods for spatial-temporal analysis. Dr. Wan Fairos has published over 30 papers in renowned journals and conferences, with her work cited in over 400 papers (H-Index 12). She is an associate fellow of the Institute of Big Data Analytics and Artificial Intelligence and a fellow of the Malaysian Institute of Transport. She has led multiple government-funded research projects and is a certified Rapid Miner Data Analyst. Dr. Wan Fairos is also a frequent invited speaker at workshops and conferences on panel count models and data mining.
WORKSHOP
Assoc.Prof. Dr. Wong Kah Keng
University Lecturer, Universiti Sains Malaysia
CRAFTING PUBLISHABLE GRAPHS WITH R AND BIOCONDUCTOR
"Crafting Publishable Graphs with R and Bioconductor" is a 2-hour pre-conference workshop. Participants will learn to create publication-quality graphs for biomedical research using R and Bioconductor. The session covers various chart types including scatter plots, heatmaps, and volcano plots, helping researchers effectively visualize their data.
Dr. Yu Yong Poh
MyRUG Committee, Deputy Director at Tunku Abdul Rahman University of Management and Technology
EMPOWERING R WITH GENERATIVE AI: A PRACTICAL EXPLORATION
This workshop dives into the exciting synergy between R and generative AI. We'll cover practical techniques for integrating AI models into R workflows, enabling tasks like:
Automated code generation: Streamline development and enhance productivity
Data exploration and visualization: Uncover hidden insights in complex datasets
Text analysis and generation: Create dynamic reports and summaries
Through hands-on examples, you'll gain the skills to leverage AI's creative potential within the R ecosystem. Whether you're a data scientist, researcher, or enthusiast, this workshop will open doors to innovative possibilities.
Talk
Prof. Dr. Kamarul Imran
Professor in Epidemiology and Statistics, Universiti Sains Malaysia
Research Coordinator, RCMO USM Health Campus
TEACHING AND LEARNING R: SOME TIPS
Professor Dr. Kamarul Imran Musa is a medical epidemiologist and biostatistician at Universiti Sains Malaysia. He obtained PhD (Epidemiology and Statistics) from Lancaster University, UK and after coming back to Malaysia, he introduced R in the academic syllabus. He runs regular R workshops locally and has attended multiple R workshops in the Europe.
Dr. Mohammad Nasir Abdullah
Senior Lecturer, Universiti Teknologi Mara
AUTOMATED MACHINE LEARNING (AutoML) WITH R: STREAMLINING THE MODEL BUILDING PROCESS
In this talk, Automated Machine Learning (AutoML) with R: Streamlining the Model Building Process, AutoML will be introduced, highlighting its importance in automating tasks such as feature selection and hyperparameter tuning to streamline model development. Using the H2O package in R, a demonstration will showcase how AutoML enables efficient and scalable machine learning by running multiple algorithms and selecting the best model, providing attendees with practical knowledge to apply AutoML in their own projects.
Dr. Mohamad Afiq Amsyar Bin Hamedin
Doctor of Public Health (Epidemiology) Candidate, Universiti Sains Malaysia
R-INLA FOR SPATIAL DATA ANALYSIS
In this session, we delve into the transformative potential of Integrated Nested Laplace Approximations (INLA) for spatial analysis in public health. By leveraging the R-INLA package, we will explore how to model complex spatial dependencies, uncover hidden patterns, and make robust inferences that can inform public health interventions. Whether you're tackling disease mapping, environmental risk assessment, or health outcomes research, this talk will equip you with practical insights and tools to elevate your spatial analysis workflows in R.
Dr. Tengku Muhammad Hanis Bin Tengku Mokhtar
Founder And Academic Trainer, Jom Research
EXPLORING THE COVID-19 RESEARCH LANDSCAPE IN MALAYSIA: A BIBLIOMETRIC CASE STUDY
The COVID-19 pandemic led to a global surge in scientific research, and Malaysia was no exception. This talk presents a bibliometric analysis of Malaysia’s COVID-19-related research, using data from the Web of Science database. Bibliometric analysis, which quantitatively evaluates publications through metrics like citation counts, publication volume, and collaboration networks, provides insights into key research trends, influential contributors, and collaborative efforts. By employing R and Python for the analysis, this case study demonstrates how bibliometric techniques can uncover valuable patterns and trends within Malaysia’s pandemic research landscape.
Dr. Muhammad Saufi bin Abdullah
Doctor of Public Health (Epidemiology) Candidate, Universiti Sains Malaysia
INTRODUCTION TO QUARTO
We will learn how to create reproducible reports using Quarto, understand the importance of reproducibility in data analysis and reporting, and observe how Quarto integrates code, analysis, and documentation into a single workflow.
Ts. Dr. Mohamad Arif Bin Awang Nawi
Lecturer of Biostatistics, School of Dental Sciences
Universiti Sains Malaysia
APPLYING R TO HEALTH DATA PREDICTION: OVERCOMING SMALL DATA LIMITATIONS
Ts. Dr. Mohamad Arif Awang Nawi is a Lecturer of Biostatistics at the School of Dental Sciences, Universiti Sains Malaysia (USM) and serves as the biostatistics coordinator at the USM Health Campus. He holds a BSc in Mathematics & Computing and a Master’s in Mathematical Sciences from Universiti Malaysia Terengganu (UMT), along with a PhD in Statistics from Universiti Sultan Zainal Abidin (UniSZA). “Applying R to Health Data Prediction: Overcoming Small Data Limitations" discussed strategies to improve health data predictions using R, despite small datasets. It covered techniques like data augmentation, bootstrapping, and synthetic data generation to enhance predictive accuracy and model performance. Practical case studies demonstrated these methods' effectiveness, showcasing R's capability to tackle small data challenges and improve health research outcomes.
Dr. Muhammad Jaffri Mohd Nasir
Senior Lecturer
Universiti Malaysia Kelantan
A BRIEF INTRODUCTION AND APPLICATION OF RCpp PACKAGE: MAKING R EXECUTION FASTER
Dr. Muhammad Jaffri Mohd Nasir is a Senior Lecturer at Universiti Malaysia Kelantan. His expertise lies in enhancing statistical methods for empirical problems through the development of new techniques and algorithms, alongside his passion for coding. His research interests span time series analysis, econometrics modeling, change-point estimations, graphical modeling, Markov processes, mathematical optimizations, item response theory, machine learning, and applied statistics in various fields such as business, finance, social sciences, and epidemiology. He holds a PhD in Mathematics and Statistics from The University of Western Australia, and an MSc and BSc in Applied Statistics from Universiti Teknologi MARA.
Ts. Dr. Liew Kok Jun (James)
Senior Bioinformatician, Codon Genomics Sdn. Bhd.
PRACTICAL APPLICATIONS OF R IN GENOMICS: A COMMERCIAL PERSPECTIVE WITH LIVE GRAPH DEMO
Ts. Dr. Liew Kok Jun, known as James, is a Senior Bioinformatician at Codon Genomics Sdn. Bhd. He holds a Bachelor of Science (Honours) in Biotechnology from Universiti Tunku Abdul Rahman, as well as a Master of Science (MSc) and Doctor of Philosophy (Ph.D.) from Universiti Teknologi Malaysia. His expertise spans microbiology, molecular biology, protein science, next-generation sequencing, and bioinformatics. Over the course of his research career, Dr. Liew has excelled in analyzing prokaryotic and eukaryotic genomes and transcriptomes, with a special focus on amplicon and shotgun metagenomics studies.
With an h-index of 7, Dr. Liew has made significant contributions to understanding microbial diversity in various environmental samples such as hot springs, biofilms, seawater, and peat soil. His notable work includes pioneering the recovery of metagenome-assembled genomes (MAGs) from Malaysian hot spring biofilms, emphasizing his expertise in omics technologies. His publications reflect his dedication to advancing the field, with significant focus on transcriptomics. Notably, his research delves into the transcriptomic responses of pathogens like Candida albicans, Pseudomonas aeruginosa, and Staphylococcus aureus to plasma medicine.
Currently, Dr. Liew is integrating R programming into his transcriptomics research, applying advanced R techniques for data analysis and visualization. His work with R has been instrumental in enhancing the depth of his transcriptome studies, allowing for more robust and efficient data interpretation. He is also exploring the application of machine learning and AI-driven bioinformatics to study environmental microbiomes, agriculture, and horticulture, with the aim of driving future innovations. His ongoing efforts promise new insights with significant scientific and practical implications.
In this talk, Ts. Dr. Liew Kok Jun (James), Senior Bioinformatician at Codon Genomics Sdn. Bhd., will showcase the practical applications of R in genomics, with a focus on transcriptome analysis. Using real-world examples, he will demonstrate how R is applied in commercial settings to process and analyze RNA-Seq data. Attendees will learn how R enhances cost-efficiency and scalability in genomic projects. The session will conclude with a live demo on creating insightful visualizations from transcriptome data using ggplot2, offering a hands-on glimpse into R’s powerful capabilities for genomics research and commercial use.
Dr. Mohd Azmi bin Suliman
Public Health Medicine Specialist, National Institutes of Health (NIH)
IMPLEMENTING AND ANALYZING COMPLEX SAMPLING DESIGN IN NATIONAL HEALTH AND MORBIDITY SURVEY USING R
Dr Mohd Azmi previously worked in the Disease Control Division, Ministry of Health Malaysia. As part of his postgraduate training, he was formally trained in disease prevention, disease modelling, clinical epidemiology, and clinical research. His previous research project involved studying the burden of stroke caregivers and modelling the trend of burden.
The National Health and Morbidity Survey (NHMS) assesses the health status of Malaysians using a survey approach to reduce costs, unlike a full census. To ensure national representativeness, NHMS applies complex sampling methods, such as stratification and clustering, which affect sampling probabilities. The weights also account for non-response, leading to more accurate population estimates. R’s survey package analyses weighted data and provides precise results from the complex sampling design.
R-Ladies
Dr. Gan Chew Peng
Senior Lecturer, Taylor's University
UNLOCKING THE POWER OF R FOR CREDIT RISK MODELING: A DEEP DIVE
This talk will explore the diverse applications of R in credit risk modeling, showcasing its capabilities in tackling various challenges throughout the modeling lifecycle. We'll delve into real-world examples and best practices, highlighting R's strengths in data manipulation, model development, validation, and visualization.
Dr. Hazlienor Binti Mohd Hatta
Doctor of Public Health (Epidemiology) Candidate, Universiti Sains Malaysia
SPATIAL EPIDEMIOLOGY USING R
Spatial epidemiology is the study of the spatial distribution of diseases, focusing on identifying geographic patterns in health outcomes to inform public health interventions. Using R, spatial epidemiology enables researchers to analyze the relationship between location, environmental factors, and disease risk. This talk will introduce key concepts, including spatial data types, coordinate reference systems (CRS), and spatial autocorrelation. It will also cover R packages like sf, sp, and ggplot2 for data manipulation and visualization. By integrating spatial analysis into public health, researchers can gain valuable insights into disease dynamics, helping to improve surveillance, prevention, and control strategies.
Dr. Nik Nur Fatin Fatihah Sapri
Lecturer, Universiti Teknologi MARA
R FOR SPATIAL-TEMPORAL ANALYSIS AND MIXED MODEL
The spatio-temporal model using the Bayesian method has been widely used in epidemiology, disease mapping and environmental studies. Using the CARBayesST package in R, this talk will demonstrate how the spatial and temporal Bayesian Poisson Generalised Linear Mixed Model offers a better model for predicting dengue incidence as compared to the conventional model. Furthermore, the power of the tmap package in R will be showcased, highlighting its ability to create detailed and informative spatial maps, thereby enriching the visual representation and analysis of spatial data.
Wan Shakira Rodzlan Hasani
Researcher at Institute for Public Health (IPH), National Institutes of Health (NIH)
PhD (Biostatistics), MSc (Medical Statistics)
META-ANALYSIS USING R
This 30-minute session will introduce the key concepts of systematic review and meta-analysis, with a focus on their importance in evidence-based research. Participants will learn how to use R’s meta and metafor packages to perform meta-analyses, transforming complex datasets into well-supported conclusions. The presentation will cover essential analytical steps, making it valuable for both experienced researchers and those new to meta-analysis.