Professor Dr.
 Rayner Alfred
Professor Dr. Rayner Alfred
Fakulti Komputeran Dan Informatik · Fakulti Komputeran Dan Informatik, UMS
ralfred@ums.edu.my
Summary

Professor Dr. Rayner Alfred is a distinguished researcher at Fakulti Komputeran Dan Informatik, University Malaysia Sabah. Their research focuses on Machine Learning and Machine Intelligence, Natural Language Processing, Information Retrieval, Sentiment Analysis, Knowledge Discovery in Big Data, Big Data Analytics, Data Science, Businness Intelligence, Data Visualization .

As a member of Fakulti Komputeran Dan Informatik, they contribute significantly to the academic and research community at UMS through their expertise and dedication to advancing knowledge in their field.

Professor Dr. Rayner Alfred holds PhD from York University, UK , among other qualifications, and has established themselves as a respected expert in their field.

Education
Phd
Msc
Bsc
Stats
Publications:
262
Projects:
11
Grants:
RM 1,433,828.60
Scopus Metrics
Scopus Author ID:
24722539300
H-Index:
20
Documents:
196
Citations:
1,418
Research Interests
INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) - Knowledge Representation and Machine Learning
INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) - Quantum Computing
INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) - Computational Modelling and Analytics
MANUFACTURING AND INDUSTRIAL ENGINEERING - Artificial Intelligence and Optimisation Methods
STATISTICAL STUDIES - Computational Artificial Neural Networks
Latest Grants
Machine Intelligence Revolutionized Storage And Shipping Tank For Aquaculture Sea Products To Support The Development Of A Sustainable Blue Economy
A Smart Patient Tracking And Behavior Analytics System Using Ultra-wideband
An Integrated Conjoined Recurrent And Convolutional Neural Network Approach To Classifying Time-series Forests Hyper-spectral Images For Automated Carbon Stock Estimation.
Latest Publications
Machine Learning-powered Customer Lifetime Value Segmentation For Predicting Customer Value In The E-commerce Industry
Develop The Spatial Modeling For The Children's Internet Risk Content In Sabah
Face Recognition With Mask Using Generative Adversarial Networks And Variational Autoencoders
Optimized Tree-based Mining Contrast Subspace For Categorical Data
Enhancing Carbon Stock Estimation Using Machine Learning Models: A Comparative Analysis Of Mlp, Rnn, And Autoencoder Approaches
Previous Appointments
Administrative Positions