Assistant Professor, Faculty of Science
Dr Owais Ahmed Malik is an Assistant Professor in Mathematical and Computing Sciences department at Faculty of Science, Universiti Brunei Darussalam (UBD). He completed his PhD in Computer Science from Universiti Brunei Darussalam (2015), MS in Computer Science from KFUPM, Saudi Arabia (2002) and BE is Computer Systems Engineering from NED, Pakistan (1998). Dr Owais has more than ten years of progressive experience in academia and research in the field of computer science and engineering. He has been teaching various undergraduate courses including machine learning, data mining, machine perception, programming fundamentals, design and analysis of algorithms, software engineering and operating system in different national/international universities. His research interest includes designing and exploring different intelligent/pattern recognition algorithms for the analysis and classification of biodiversity and Cyber-security data, applied biomechanics, bio-signal processing and big data analytics. He has published a number of articles in internationally reputable journals and conferences.
PhD (Computer Science - Machine Learning and Sensors in Health Systems), MSc (Computer Science - AI for Planning/Reasoning), BE (Computer Engineering)
Machine Learning, Data Mining, Computer Vision/Image Processing, Deep Learning, Fuzzy Logic, Knowledge Based Systems, Intelligent Decision Support Systems for Rehabilitation Monitoring, Big Data Analytic, Wireless Body Area Network, Biosignal Processing and Analysis, Applied Biomechanics
This project is related to the application of machine learning techniques in the field of biodiversity (especially plants and herbs).
This project is related to the application of mixed reality and computational modeling and/or simulation for various fields including e-learning, education, computational chemistry and biology.
For details contact thru email.
Google Scholar Citations
Google Scholar h-index
Google Scholar i10-index
Semantic Segmentation of Herbarium Specimens Using Deep Learning Techniques, BR Hussein, OA Malik, WH Ong, JWF Slik - Computational Science and Technology, 2020, Lecture Notes in Electrical Engineering, vol 603. Springer, Singapore
Automated Classification of Tropical Plant Species Data Based on Machine Learning Techniques and Leaf Trait Measurements, BR Hussein, OA Malik, WH Ong, JWF Slik - Computational Science and Technology, 2020, Lecture Notes in Electrical Engineering, vol 603. Springer, Singapore
Integrated TOC prediction and source rock characterization using machine learning, well logs and geochemical analysis: Case study from the Jurassic source rocks in Shams Field, NW Desert, Egypt, MR Shalaby, N Jumat, D Lai, O Malik - Journal of Petroleum Science and Engineering, 2019
Machine-Learning-Based Cyclic Voltammetry Behavior Model for Supercapacitance of Co-Doped Ceria/rGO Nanocomposite, S Parwaiz, OA Malik, D Pradhan, MM Khan - Journal of chemical information and modeling, 2018
Identifying sub-groups of the obese from national health and nutritional status survey data using machine learning techniques', Khalil, U.; Malik, O.A.; Lai, D.; King, O.S., IET Conference Proceedings, 2018, p. 113 (4 pp.)-113 (4 pp.), IET Digital Library
An Intelligent Recovery Progress Evaluation System for ACL Reconstructed Subjects Using Integrated 3-D Kinematics and EMG Features
OA Malik, SMN Senanayake, D Zaheer, IEEE Journal of Biomedical and Health Informatics, 1-1, 2015
A Multisensor Integration-Based Complementary Tool for Monitoring Recovery Progress of Anterior Cruciate Ligament-Reconstructed Subjects
OA Malik, SMN Arosha Senanayake, D Zaheer, IEEE/ASME Transactions on Mechatronics, 2014
A knowledge-based intelligent framework for anterior cruciate ligament rehabilitation monitoring
SMN Arosha Senanayake, OA Malik, PM Iskandar, D Zaheer, Applied Soft Computing 20, 127-141, 2013
Software level green computing for large scale systems
F Fakhar, B Javed, R ur Rasool, O Malik, K Zulfiqar, Journal of Cloud Computing: Advances, Systems and Applications 1 (1), 4, 2012
A hybrid intelligent system to improve predictive accuracy for cache prefetching
S Sarwar, Z Ul-Qayyum, OA Malik, Expert Systems with Applications 39 (2), 1626-1636, 2012
Automated Realtime Plant Species Recognition Using State of The Art Machine Learning Techniques (UBD/RSCH/1.4/FICBF((b)/2018/011
S.M.N. Arosha Senanayake and Owais Ahmed Malik, 2014, "Real Time Biofeedback Mechanism and Data Presentation for Knee Injury Rehabilitation Monitoring and a Soft Real Time Intelligent System Thereof", US Patent - 10004455 B2, June 26 2018, Brunei Patent BN/N/2014/0036 â€“ World Intellectual Property Organization (WIPO).
Ministry of Health, Brunei Darussalam