University of Nottingham Malaysia
School of Computer Science
     
  
 

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Doreen Ying Ying Sim

Assistant Professor,

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Biography

Dr. Sim acquired her PhD degree (Doctor of Philosophy) in Data Mining, Machine Learning and Computational Intelligence after acquiring her M.Sc. degree in Business Information Technology from University of Portsmouth, United Kingdom and B.Sc.(Honors) degree in Business Information Technology from University of Central England in Birmingham, United Kingdom. Dr. Sim also acquired double major degrees in Medical Sciences, ie. in Pharmacology and Physiology, from University of Otago, Dunedin, New Zealand. Dr. Sim has around 23 years of lecturing and research experiences in the tertiary education industry, i.e. in both public and private universities. For research publications, Dr. Sim has done a lot of researches in using Machine Learning techniques to develop prediction and early detection algorithms in the medical field such as in Obstructive Sleep Apnea, Human-Computer Interaction, Computational Intelligence, Human-Robot Interaction and Robotics, i.e. part of Artificial Intelligence.

Expertise Summary

My main research interests embark in Data Mining, Machine Learning and Computational Intelligence. Currently, I am doing a lot of researches in EEG, ECG, EOG and EMG as well as in developing prediction and early detection algorithms for medical diagnoses such as for Obstructive Sleep Apnea.

Teaching Summary

Dr Sim has more than 21 years of professional lecturing experience in IT and Computer Science in the tertiary education industry, i.e. mainly in public and private universities.

Recent Publications

  • DOREEN YING YING SIM, CHEE SIONG TEH AND AHMAD IZUANUDDIN ISMAIL, 2022. Effective k-Means Clustering in Greedy Pre-pruned Tree-based Classification for Obstructive Sleep Apnea International Journal of Electrical and Electronic Engineering & Telecommunications. 11(3), 242-248
  • DOREEN YING YING SIM, CHEE SIONG TEH and AHMAD IZUANUDDIN ISMAIL, 2020. Correlation Feature Selection Weighting Algorithms for Better Support Vector Classification: An Empirical Study Solid State Technology. 63(2s), 2794-2805
  • DOREEN YING YING SIM, 2020. In: Redefining the white-box of k-nearest neighbor support vector machine for better classification Springer, Singapore. 157-167
  • DOREEN YING YING SIM, CHEE SIONG TEH AND AHMAD IZUANUDDIN ISMAIL, 2019. Pushing Visualization Effects into Pushed Schema Enumerated Tree-Based Support Constraints Applied Mechanics and Materials. 892, 219-227

School of Computer Science

University of Nottingham Malaysia
Jalan Broga, 43500 Semenyih
Selangor Darul Ehsan
Malaysia

telephone: +6 (03) 8924 8000
fax: +6 (03) 8924 8018

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