Associate Professor Dr. Rayner Alfred
Biography (Curriculum Vitae)
Rayner Alfred is an Associate Professor of Computer Science at the Faculty of Computing and Informatics, Universiti Malaysia Sabah in Malaysia. Rayner completed his PhD in 2008 looking at intelligent techniques using machine learning to model and optimize the dynamic and distributed processes of knowledge discovery for structured and unstructured data. He holds a PhD degree in Computer Science from York University (United Kingdom), a Master degree in Computer Science from Western Michigan University, Kalamazoo (USA) and a Computer Science degree from Polytechnic University of Brooklyn, New York (USA) where he was the recipient of the Myron M. Rosenthal Academic Achievement Award for the outstanding academic achievement in Computer Science in 1994. He has been a visiting scholar at Korea Institute of Advanced Study, Seoul, KOREA in 2020, Japan Advanced Institute of Science and Technology, JAPAN in 2018 and he is a member of board of directors, MIMOS (Malaysian Institute of Microelectronic Systems) from 2019 to 2021.
He leads and defines projects around knowledge discovery, information retrieval and machine learning that focuses on building smarter mechanism that enables knowledge discovery in structured and unstructured data. His work addresses the challenges related to big data problem: How can we create and apply smarter collaborative knowledge discovery and machine learning technologies that bridge the structured and unstructured data mining and cope with the big data problem. He has been a chair for computational science and machine learning conferences such as Computational Science and Technology (ICCST), Computational Science and Engineering (ICCSE) and Advanced Information System and Knowledge Management (AISKM).
He has authored and co-authored more than 150 journals/book chapters and conference papers, editorials, and served on the program and organizing committees of numerous national and international conferences and workshops. In terms of postgraduate student supervision, he has successfully supervised 6 doctorate and 7 master students. Now, he has 9 active PhD students undergoing research in Biometric security, Big Data Analytics, Data Modelling and Visualization, Machine Learning for Odour Classification, Multi-Agent Technology and Digital Transformation.
Rayner is currently a member of IEEE, a Certified Software Tester (CTFL) from the International Software Testing Qualifications Board (ISTQB), and also a certified IBM DB2 Academic Associate (IBM DB2 AA). He leads the Advanced Machine Intelligence (AMI) research group in UMS and he has lead several projects related to knowledge discovery and machine learning on Big Data. He is also the recipient of multiple GOLD and SILVER awards at national and international research exhibitions in Data Mining and Machine Learning based solutions (Face Recognition and Knowledge Discovery), that include International Trade Fair Ideas in Nuremberg, Germany (iNEA2018, iENA2019) International Invention Innovation Competition in Toronto, Canada (iCAN 2018), Seoul International Invention Exhibition in Seoul, Korea (SIIF 2010), International Conference and Exposition on Inventions by Institutions of Higher Learning (PECIPTA2019, PECIPTA2010) and International Invention, Innovation & Technology Exhibition, Malaysia (ITEX2019, ITEX2018 and ITEX2010).
He has secured RM6,931.433.00 worth of project grants. Some of his project researches include biometric authentication using face recognition, building security based on plate number recognition using deep learning, sentiment analysis for Malay and English in measuring public opinion, news-news correlation trending, machine learning algorithm-based solution for predicting diseases in health care, smart monitoring using an ensemble-based face recognition system and smart information management and retrieval to name a few. Some of the completed projects include Semantic Multi-Agent For Knowledge Sharing, developing an Evolutionary-Based Ensemble Classifier Framework for Learning Big Relational Data, developing a genetic-based hierarchical agglomerative clustering technique for parallel clustering of bilingual corpora based on reduced terms, enhancing document Clustering By Integrating Semantic Background Knowledge and Syntactic Features Into the BOW Representation and the fundamental Study on an Evolutionary Based Features Construction Methods for Data Summarization Approach to Predict Survival Factors of Coral Reefs in Malaysia, to name a few and also infrared face recognition based on ensemble approach.
He has also delivered several keynote speeches to the public and private sectors on Embracing the Wave of IR4.0 for Smart Farming, Transforming e-Government to Smart Government, Industrial Revolution 4.0, Digital Transformation, e-Commerce and Research and Innovation, and finally the vital area skills and factors for effective digital transformation towards smart Sabah government.
He leads and defines projects around knowledge discovery, information retrieval and machine learning that focuses on building smarter mechanism that enables knowledge discovery in structured and unstructured data. His work addresses the challenges related to big data problem: How can we create and apply smarter collaborative knowledge discovery and machine learning technologies that bridge the structured and unstructured data mining and cope with the big data problem. He has been a chair for computational science and machine learning conferences such as Computational Science and Technology (ICCST), Computational Science and Engineering (ICCSE) and Advanced Information System and Knowledge Management (AISKM).
He has authored and co-authored more than 150 journals/book chapters and conference papers, editorials, and served on the program and organizing committees of numerous national and international conferences and workshops. In terms of postgraduate student supervision, he has successfully supervised 6 doctorate and 7 master students. Now, he has 9 active PhD students undergoing research in Biometric security, Big Data Analytics, Data Modelling and Visualization, Machine Learning for Odour Classification, Multi-Agent Technology and Digital Transformation.
Rayner is currently a member of IEEE, a Certified Software Tester (CTFL) from the International Software Testing Qualifications Board (ISTQB), and also a certified IBM DB2 Academic Associate (IBM DB2 AA). He leads the Advanced Machine Intelligence (AMI) research group in UMS and he has lead several projects related to knowledge discovery and machine learning on Big Data. He is also the recipient of multiple GOLD and SILVER awards at national and international research exhibitions in Data Mining and Machine Learning based solutions (Face Recognition and Knowledge Discovery), that include International Trade Fair Ideas in Nuremberg, Germany (iNEA2018, iENA2019) International Invention Innovation Competition in Toronto, Canada (iCAN 2018), Seoul International Invention Exhibition in Seoul, Korea (SIIF 2010), International Conference and Exposition on Inventions by Institutions of Higher Learning (PECIPTA2019, PECIPTA2010) and International Invention, Innovation & Technology Exhibition, Malaysia (ITEX2019, ITEX2018 and ITEX2010).
He has secured RM6,931.433.00 worth of project grants. Some of his project researches include biometric authentication using face recognition, building security based on plate number recognition using deep learning, sentiment analysis for Malay and English in measuring public opinion, news-news correlation trending, machine learning algorithm-based solution for predicting diseases in health care, smart monitoring using an ensemble-based face recognition system and smart information management and retrieval to name a few. Some of the completed projects include Semantic Multi-Agent For Knowledge Sharing, developing an Evolutionary-Based Ensemble Classifier Framework for Learning Big Relational Data, developing a genetic-based hierarchical agglomerative clustering technique for parallel clustering of bilingual corpora based on reduced terms, enhancing document Clustering By Integrating Semantic Background Knowledge and Syntactic Features Into the BOW Representation and the fundamental Study on an Evolutionary Based Features Construction Methods for Data Summarization Approach to Predict Survival Factors of Coral Reefs in Malaysia, to name a few and also infrared face recognition based on ensemble approach.
He has also delivered several keynote speeches to the public and private sectors on Embracing the Wave of IR4.0 for Smart Farming, Transforming e-Government to Smart Government, Industrial Revolution 4.0, Digital Transformation, e-Commerce and Research and Innovation, and finally the vital area skills and factors for effective digital transformation towards smart Sabah government.
