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The daily life of a PhD student may differ significantly from that of an undergraduate or Masters student. There will be much more independence and very few 'taught' elements. A typical week will almost certainly include the same number of PhD study hours as a full-time job. This page will give you an idea of what daily routine will be like as a PhD student. You can see my students' sharing materials.
Winarni, S., Indratno, S. W., Othman, M. S., Mohd Hashim, S. Z., Mohamad, M. M., et al. (2026). Enhancing symbolic image classification through Gaussian copulas and optimized distinguishing points. PLOS ONE. https://doi.org/10.1371/journal.pone.0346790
Zhu, L., Yusuf, L. M., & Othman, M. S. (2026). Adoption and effective use of management information systems in Chinese higher education (faculty attitudes, motivations and barriers): Evidence from Hebei province. Humanities and Social Sciences Communications. [https://doi.org/10.1057/s41599-026-06807-x]
Li, J., Othman, M. S., Ying, X., Hassan, D. S. M., Chen, H., & Yusuf, L. M. (2026). Adaptive NetFlow IIoT intrusion detection with deep transfer learning, genetic optimization, and ensemble methods for network management. IEEE Transactions on Network and Service Management. [https://doi.org/10.1109/TNSM.2025.3617765]
Adeyemo, S. O., Othman, M. S., Chan, W. H., Almarshadi, M. S., Mohd Hashim, S. Z., Tafa, T. O., & Yalwa, A. S. (2026). A deployment-oriented framework for machine learning-based learning style identification: A systematic computational analysis. International Journal of Advanced Computer Science and Applications, 17(3) [https://doi.org/10.14569/IJACSA.2026.0170367].
Yang, X., Othman, M. S., Tian, L., Liang, C., Qi, D., & Wang, D. (2026). Developing digitalized green and low-carbon accounting: A case study of Guiyang City. In Proceedings of the 2025 4th International Conference on Mathematical Statistics and Economic Analysis (MSEA 2025) (pp. 98–109). Atlantis Press. [https://doi.org/10.2991/978-94-6463-992-6_11]
Jailani, N. S., Mohamad, M. M., Munajat, M. D. E., Irawati, I., Nurasa, H., et al. (2026). Explainable artificial intelligence (XAI) for interpretable heritage building maintenance prediction. In Proceedings of the 2025 International Conference on AI-Driven Business Transformation and Data Science Innovation (ICBTDS 2025). ACM. [https://doi.org/10.1145/3786554.3786572]
Phd students
Computer Science
No
Name
Title
File
1
Li Jing
Optimized Attack Classification Framework for Internet of Things Security using Feature Selection and Deep Transfer Learning
2
Rozilawati Dollah @ Md Zain
An Ontology Based Model for Biomedical Text Classification
3
Shamini Raja Kumaran
Enhanced Classification Techniques Based on Gene Manipulation for Cancer Microarray Data
4
Dewi Octaviani
Semantic Model for Mining E-Learning Usage with Ontology and Meaningful Learning Characteristics
5
Bahram Amini Valashani
An Ontology-Based Recommender System using Scholar’s Background Knowledge
6
Arda Yunianta
Ontology-Based Semantic Heterogeneous Data Integration Framework for Learning Environment
Other student
No
Name
Title
File
1
Xu Deren
Blended Ensemble Model for Prediction of Infectious Diseases
Social Science
No
Name
Title
File
1
Zhu Linnan
A User Related Determinant Model In Management Information System For China Higher Education
2
Ernie Mazuin Mohd Yusof
Individual Level Determinants Model for Benefit Use of Business Intelligence in Malaysia Manufacturing Organizations
3
Qusay Sabah Ishaq Al-Maatouk
Social Media Utilization Model for the Improvement of Academic Performance at Malaysian Higher Education Institutions
4
Nur Shamsiah Abdul Rahman
A Model of Behaviour Intention Factors on Social Media Use for Collaborative Learning Affecting Teaching and Learning
5
Waleed Mugahed Ali Al-Rahmi
The Impact of Social Media Use in Collaborative Learning Towards Learning Performance Among Research Students
6
Mahdi Alhaji Musa
Knowledge Map, Enterprise Ontology and Lean for enhancing Business Process Re-Engineering in Healthcare
📖 Phd: Proposal
No
Name
Title
File
1.
Abdulaziz Saidu Yalwa
Modelling Students’ Continuance Intention to Use Generative AI in Higher Education
2.
Adeyemo Sarafa Olasunkanmi
Enhanced Learning Styles Identification Using Ensemble Deep Learning Techniques With Multimodal Data
3.
Taofik Olasunkanmi Tafa
Optimised Multimodal Approach For Neural Machine Translation Of Low-Resource Languages
4.
Apri Junaidi
Enhancing Rice Leaf Disease Detection: A Comprehensive Approach to Image Noise Reduction, Multi-Object Identification, and Small Object Detection
5.
Zhu Chaihua
A Model of Customer Stickiness for Cross-Border Social E-Commerce Platform in China
6.
Zhu Linnan
Investigating User Factors in Management Information System Adoption and Implementation in Higher Education Institutions
7.
Li Jing
Enhanced Attack Detection and Classification Techniques Based on Feature Manipulation of IOT Data for IOT Security
8.
Saleh Dhekre Saber Saleh
A Predictive Analysis Framework of Thyroid Disease Using Machine Learning Approaches
📖 MSc Data Science
No
Name
Title
File
1.
Nur Afrina Binti Mohamad Abdul Ghafar
Cooking Oil Price Forecasting Using SARIMA and LSTM in Malaysia
2.
Abubakar Sadiq Muahammad
Sentiment Analysis and Rating Prediction for an E-Commerce Platforms in Malaysia using CNN and LSTM
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The daily life of a PhD student may differ significantly from that of an undergraduate or Masters student. There will be much more independence and very few 'taught' elements. A typical week will almost certainly include the same number of PhD study hours as a full-time job.