Mohamed Ragab

scientist---mohamed-ragab

Research Area
  • Deep Learning
  • Transfer Learning
  • Domain Adaptation
  • Time-series Data
  • Predictive Maintenance

Award

  • Finalist Paper Award at International Conference of Prognostics and Health Management - July, 2020
  • Singapore International Graduate Award (SINGA) - August, 2018
  • Best Master’s Thesis Award - August, 2017
  • First Class Honours Award at Bachelor’s Degree - July, 2014

Publications

Journal Papers

1. Mohamed Ragab, Emadeldeen Eldele , Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li. Self-supervised Autoregressive Domain Adaptation for Time Series Data. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.

2. Emadeldeen Eldele , Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li and Cuntai Guan. ADAST: Attentive Cross-domain EEG-based Sleep Staging Framework with Iterative Self-Training. IEEE Transactions on Emerging Topics in Computational Intelligence, 2022.

3. Mohamed Ragab, Zhenghua Chen, Wenyu Zhang, Emadeldeen Eldele, Min Wu, Chee-Keong, Kwoh, Xiaoli Li. Conditional Contrastive Domain Generalization Towards Real-world Fault Diagnosis. IEEE Transactions on Instrumentation and Measurement, 2022.

4. Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li. Attention Based Sequence to Sequence Model for Remaining Useful Life Prediction. Neurocomputing, Elsevier, 2021.

5. Mohamed Ragab, Zhenghua Chen, Min Wu, Chuan-Sheng Foo, Chee-Keong, Kwoh, Ruqiang Yan, Xiaoli Li. Contrastive Adversarial Domain Adaptation for Machine Remaining Useful Life Prediction. IEEE Transactions on Industrial Informatics, 2021.

6. Mohamed Ragab, Zhenghua Chen, Haoliang Li, Min Wu, Chee-Keong Kwoh, Xiaoli Li. Adversarial Multiple-Target Domain Adaptation for Fault Diagnosis. IEEE Transactions on Instrumentation and Measurement, 2021.

7. Qing Xu, Zhenghua Chen, Mohamed Ragab, Chao Wang, Min Wu, Xiaoli Li. Contrastive Adversarial Knowledge Distillation for Deep Model Compression in Time-Series Regression Tasks. Neurocomputing, 2021.

8. Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li and Cuntai Guan. Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021. (Under-review)

9. Mohamed Ragab, Osama A. Omer, Mohamed Abdel-Nasser. Compressive Sensing MRI Reconstruction Using Empirical Wavelet Transform and Grey Wolf Optimiser. Neural Computing and Applications, 2018.

Conference Papers

1. Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li, and Cuntai Guan. Time-Series Representation Learning via Temporal and Contextual Contrasting. International Joint Conference of Artificial Intelligence, IJCAI, 2021.

2. Wenyu Zhang, Mohamed Ragab, Ramon Sagarna. Robust Domain-free Domain Generalization with Class-aware Alignment. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021)

3. Chao Jin, Mohamed Ragab, Khin Mi Mi Aung. Secure Transfer Learning for Machine Fault Diagnosis under Different Operating Conditions. International Conference on Provable and Practical Security (PROVSEC 2020)

4. Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li. Adversarial Transfer Learning for Remaining Useful Life Estimation. IEEE International Conference on Prognostics and Health Management (ICPHM 2020), (Finalist Award).

5. Mohamed Ragab, Osama A. Omer, Hany S. Hussien. Compressive Sensing MRI Using Dual Tree Complex Wavelet Transform with Wavelet Tree Sparsity. 34rd National Radio Science Conference (NRSC), 2017

Research Services

Journal Invited Reviewer

  • IEEE Transactions on Neural Networks and Learning Systems
  • IEEE Transactions on Instrumentation and Measurements
  • IEEE Sensors
  • IEEE Transactions on industrial informatics
  • Reliability Engineering
  • Neurcomputing

Program Committee Member

  • International Joint Conference of Artificial Intelligence (IJCAI), 2022
  • Association for the Advancement of Artificial Intelligence (AAAI), 2022