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Anwar P.P. Abdul Majeed
PeerJ Author & Reviewer
830 Points

Contributions by role

Author 740
Reviewer 90

Contributions by subject area

Human-Computer Interaction
Artificial Intelligence
Brain-Computer Interface
Data Mining and Machine Learning
Robotics
Bioinformatics
Neuroscience
Neurology
Computer Vision
Data Science
Embedded Computing
Emerging Technologies
Algorithms and Analysis of Algorithms
Autonomous Systems
Optimization Theory and Computation
Visual Analytics

Anwar P.P. Abdul Majeed

PeerJ Author & Reviewer

Summary

Anwar P.P. Abdul Majeed graduated with a first-class honours B.Eng. in Mechanical Engineering from Universiti Teknologi MARA (UiTM), Malaysia. He obtained an MSc. in Nuclear Engineering from Imperial College London, United Kingdom. He then received his PhD in Rehabilitation Robotics from the Universiti Malaysia Pahang (UMP). He is currently serving as an Associate Professor at the School of Robotics, XJTLU. Prior to joining XJTLU, he was a Senior Lecturer (Assistant Professor) and the Head of Programme (Bachelor of Manufacturing Engineering Technology (Industrial Automation)) at the Faculty of Manufacturing and Mechatronics Engineering Technology, UMP. He is also currently serving as an adjunct lecturer at UCSI University, Malaysia. Dr Anwar is also a Visiting Research Fellow at EUREKA Robotics Centre, Cardiff Metropolitan University, UK. His research interest includes rehabilitation robotics, computational mechanics, applied mechanics, sports engineering, renewable and nuclear energy, sports performance analysis as well as machine learning. Anwar has authored over 100 papers in different journals, conference proceedings as well as books. He serves as a reviewer a number of prolific journals such as IEEE Access, Frontiers in Bioengineering and Biotechnology, PeerJ Computer Science, SN Applied Sciences, Applied Computing and Informatics amongst others. He has also served as a Guest Editor for SN Applied Sciences as well as an Editor for several Springer book series. He is also a Chartered Engineer with the Institution of Mechanical Engineers (IMechE), UK, a Member of the Institution of Engineering and Technology (IET), UK, as well as a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE).

Artificial Intelligence Data Mining & Machine Learning Emerging Technologies

Work details

Senior Lecturer

Universiti Malaysia Pahang
May 2018
Faculty of Manufacturing and Mechatronics Engineering Technology

Websites

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PeerJ Contributions

  • Articles 6
September 29, 2021
Diagnosis of hearing deficiency using EEG based AEP signals: CWT and improved-VGG16 pipeline
Md Nahidul Islam, Norizam Sulaiman, Fahmid Al Farid, Jia Uddin, Salem A. Alyami, Mamunur Rashid, Anwar P.P. Abdul Majeed, Mohammad Ali Moni
https://doi.org/10.7717/peerj-cs.638
August 18, 2021
The classification of skateboarding tricks via transfer learning pipelines
Muhammad Amirul Abdullah, Muhammad Ar Rahim Ibrahim, Muhammad Nur Aiman Shapiee, Muhammad Aizzat Zakaria, Mohd Azraai Mohd Razman, Rabiu Muazu Musa, Noor Azuan Abu Osman, Anwar P.P. Abdul Majeed
https://doi.org/10.7717/peerj-cs.680
April 7, 2021
A real-time approach of diagnosing rice leaf disease using deep learning-based faster R-CNN framework
Bifta Sama Bari, Md Nahidul Islam, Mamunur Rashid, Md Jahid Hasan, Mohd Azraai Mohd Razman, Rabiu Muazu Musa, Ahmad Fakhri Ab Nasir, Anwar P.P. Abdul Majeed
https://doi.org/10.7717/peerj-cs.432
March 31, 2021
The classification of EEG-based winking signals: a transfer learning and random forest pipeline
Jothi Letchumy Mahendra Kumar, Mamunur Rashid, Rabiu Muazu Musa, Mohd Azraai Mohd Razman, Norizam Sulaiman, Rozita Jailani, Anwar P.P. Abdul Majeed
https://doi.org/10.7717/peerj.11182 PubMed 33850667
March 2, 2021
The classification of motor imagery response: an accuracy enhancement through the ensemble of random subspace k-NN
Mamunur Rashid, Bifta Sama Bari, Md Jahid Hasan, Mohd Azraai Mohd Razman, Rabiu Muazu Musa, Ahmad Fakhri Ab Nasir, Anwar P.P. Abdul Majeed
https://doi.org/10.7717/peerj-cs.374
February 25, 2021
The classification of movement intention through machine learning models: the identification of significant time-domain EMG features
Ismail Mohd Khairuddin, Shahrul Naim Sidek, Anwar P.P. Abdul Majeed, Mohd Azraai Mohd Razman, Asmarani Ahmad Puzi, Hazlina Md Yusof
https://doi.org/10.7717/peerj-cs.379