Mohamed Ragab

Mohamed Ragab received the B.Sc. degree (First Class Hons.) in communication and electronics engineering and M.Sc. degree in medical image processing from Aswan University, Egypt, in 2014 and 2017, respectively. He is currently working toward the Ph.D. degree in computer science and engineering under the supervision of Dr. Kwoh Chee Keong, Nanyang Technological University, Singapore. He is jointly working with the Machine Intellection Department (MI), Institute of Infocomm Research (I2R), A*STAR under the supervision of Dr. Zhenghua Chen and Prof. Li Xiaoli.

Research Interests

Deep Learning
Transfer Learning
Predictive Maintenance
Intelligent Fault Diagnosis
Intelligent Fault Prognosis

Education

Doctorate of Philosophy in Computer Science and Engineering (2018-present)
- Nanyang Technological University, Singapore
Master of Science in Electrical Engineering (2015-2017)
- Aswan University, Egypt
Bachelor of Science in Electrical Engineering (2009-2014)
- Aswan University, Egypt

News

Sep-2021: Our paper entitled"Attention-Based Sequence to Sequence Model for
Machine Remaining Useful Life Prediction " has been accepted in Neurocomputing, Elsevier.
June-2021: I have been selected to participate in the first trilateral Global Fellows Programme “AI and Healthcare”, a partnership between Nanyang Technological University (NTU, Singapore), Imperial College London (UK), and Technical University of Munich (TUM, Germany).
May-2021: Our paper entitled "Time-Series Representation Learning via Temporal and Contextual Contrasting " has been accepted in International Joint Conference on Artificial Intelligence (IJCAI-21)
April-2021: Our paper entitled "Contrastive Adversarial Knowledge Distillation for Deep Model Compression in Time-Series Regression Tasks " has been accepted in Neurocomputing , Elsevier.
Jan-2021: Our paper entitled "Robust Domain-free Domain Generalization with Class-aware alignment" has been accepted at the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Oct-2020: Our paper entitled "Contrastive Adversarial Domain Adaptation for
Machine Remaining Useful Life Prediction" has been accepted by IEEE Transactions on Industrial Informatics [IF:9.112]
Sep-2020: Joined ST Aerospace as a machine learning Intern.
Sep-2020: Joined Egypt Scholars Inc. as a volunteer member at labs and communities.
Sep-2020: Our paper entitled "Secure Transfer Learning for Machine Fault Diagnosis under Different Operating Condition" has been accepted at the International Conference on Provable and Practical Security (PROVSEC 2020)
July-2020: Our paper entitled "Adversarial Multiple-Target Domain Adaptation for Fault Classification" has been accepted by IEEE Transactions on Instrumentation and Measurement
June-2020: Our paper entitled " Adversarial Transfer Learning for Machine Remaining Useful Life Prediction" has won," Finalist Academic Paper Award at IEEE International Conference on Prognostics and Health Management (ICPHM) 2020
Jan-2020: Successfully passed NTU Qualifying Exam