Halim Noor is an academic in the School of Computer Sciences at Universiti Sains Malaysia (USM). Prior to this, I served at the Universiti Teknologi MARA Pulau Pinang as a Senior Lecturer in Computer Engineering.

My research is in the fields of machine learning and deep learning for computer vision and pervasive computing. Currently, I am focusing on problems in human activity recognition and medical image analysis such as segmentation, representation (feature) learning, and prediction.

Looking forward, I am interested in

– achieving an effective segmentation of input data
– learning salient feature representation for accurate prediction
– data augmentation/generation using deep generative models

My research has been published in Journal of Ambient Intelligence and Humanized Computing, Neural Computing and Applications, Neural Processing Letters, Knowledge-based Systems, Pervasive and Mobile Computing and in the proceeding of several conferences.

Publication databases: USM Experts, Google Scholar, Scopus, Publons, ORCID, ResearchGate

Feel free to contact me to discuss any related topic or to propose a research topic.
Email: halimnoor@usm.my
Address: 610, School of Computer Sciences, Universiti Sains Malaysia


1. Nor Aizam Muhamed Yusof, Pavement Distress Analysis using Deep Learning, 2017-2021, Co-supervisor
2. Ali Olow Jimale, Enhanced Conditional Generative Adversarial Network for Handling Subject Variability In Human Activity Recognition, 2020-2023, Main Supervisor
3. Ige Ayokunle Olalekan, Deep Local-Temporal Architecture Towards Lightweight Deep Learning Activity Recognition, 2020-2023, Main Supervisor

1. Chan Mang Hong, Data Generation using Generative Adversarial Network for Human Activity Recognition, 2019, Main Supervisor
2. Jodene Ooi Yen Ling, Predicting Freezing of Gait in Parkinson’s Disease with Autoencoder-based Representation Learning, 2019, Main Supervisor
3. Loh Jing Zhi, MobileNet-SVM: A Hybrid, Light-weight Deep Learning Architecture for Human Activity Recognition, 2019, Main Supervisor
4. Yap Kah Liong, Signal Segmentation using You Only Look Once Network for Human Activity Recognition, 2019, Main Supervisor
5. Lim Chin Tiong, Comparative Study of Deep Learning-based Object Detection Algorithms on Real-time Embedded System, 2019, Main Supervisor
6. Tan Sen Yan, Hybrid Deep Learning Architecture for Activity Recognition, 2020, Main Supervisor
7. Xu Ziyue, Data Augmentation Using Improved Generative Adversarial Network for Lung Image Classification, 2022, Main Supervisor


1. Noratikah Nordin, Prediction by Machine Learning of Suicide Attempts among Adolescents in Malaysia, 2018-2023, Co-supervisor
2. Haruna Abdu, Waste Detection and Classification using Deep Learning. 2019-Present, Co-supervisor
3. Raid S. A. Basheer, Brain Connectivity Networks analysis with Graph Theory and Graph Neural Network for Brain Disorder Detection, 2019-Present, Main Supervisor
4. Abdulrahman M A Baraka, Similarity Segmentation Approach for Sensor-based Human Activity Recognition, 2020-2023, Main Supervisor
5. Fathe Said Emhemed Shaninah, Predicting Student Academic Performance using Machine Learning, 2020-Present, Main Supervisor
6. Hadeel Sameer Mohd Al Tahainah, Developing and Analyzing Artificial Intelligence-Based Algorithms for Obtaining Super Resolution Satellite Images, 2020-Present, Main Supervisor
7. Al Tabrawee Hussein Allawi Hasan, Self-supervised Learning for Human Action Recognition, 2020-Present, Main Supervisor
8. Alqablan Tamara Amjad Abdelkarim, Improved Filter-Wrapper Feature Selection Method Using Enhanced Grey Wolf Algorithm For Sentiment Analysis, 2020-Present, Main Supervisor
9. Sani Tijjani, Semi-Supervised Learning for Human Activity Recognition, 2020-Present, Main Supervisor
10. Al Kadhmawee Ahmed Adil Abdulwahid, Automated Diagnosis System of Skin Cancer Diseases Based on Machine Learning, 2021-Present, Main Supervisor
11. Itriq Mariam Abed Alfattah Ali, The Machine Translation in Natural Language Processing. 2022-Present, Main Supervisor
12. Loh Swee Kuan, The Use of Transfer Learning to Improve Performance in Smart Sampling, 2023-Present, Main Supervisor

1. Liau Wei Jie Brigitte, Semiconductor OCR Using Deep Learning, 2021-Present, Main Supervisor
2. Hazqeel Afyq Athaillah Kamarul Aryffin, The Use of Artificial Intelligence to Improve Accuracy in Triage System of Emergency Department, 2022-Present, Main Supervisor
3. Al-Battat Asaad Qasim Mahdi, Improved ResNet-50 Model with Multiscale Feature Representation for Cancer Diagnosis in Histopathological Image, 2023, Main Supervisor
4. Ammar Nayeef Makki Al-Khafaji, Adaptation of Attention Separable Convolution Residual in the U-Net Architecture for Lung Nodule Segmentation, 2023, Main Supervisor
5. Jwaber Safa Alaa Hussein, Self-supervised Visual Feature Learning for Human Action Recognition, 2023, Main Supervisor