Mohamed Ragab


PhD Student

Biography


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 
  • Machine Health Monitoring 
  • 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

Publications


Localization and Classification of Structural Damage Using Deep Learning Single-Channel Signal-Based Measurement (under review)


Majdi Flah, Mohamed Ragab, Malek Lazhari, Moncef Nehdi


Structural Health Monitoring


Attention Sequence to Sequence Model for Machine Remaining Useful Life Prediction (under review)


Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong, Kwoh, Ruqiang Yan, Xiaoli Li


IEEE Transactions on Systems, Man, and Cybernetics: Systems


Robust Domain-free Domain Generalization with Class-aware alignment (Accepted)


Wenyu Zhang, Mohamed Ragab, Ramon Sagarna


IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)


Secure Transfer Learning for Machine Fault Diagnosis Under Different Operating Conditions


Chao Jin, Mohamed Ragab, Khin Mi Mi Aung


Khoa Nguyen, Wenling Wu, Kwok Yan Lam, Huaxiong Wang, Provable and Practical Security, Springer International Publishing, Cham, 2020, pp. 278--297


Contrastive Adversarial Domain Adaptation for Machine Remaining Useful Life Prediction


Mohamed Ragab, Zhenghua Chen, Min Wu, Chuan Sheng Foo, Kwoh Chee Keong, Ruqiang Yan, Xiao-Li Li


IEEE Transactions on Industrial Informatics, 2020, pp. 1--1


Adversarial Transfer Learning for Machine Remaining Useful Life Prediction (Finalist Award)


Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li


2020 IEEE International Conference on Prognostics and Health Management (ICPHM), IEEE, 2020, pp. 1--7


View all

Contact


Mohamed Ragab


PhD Student and A*STAR Research Scholar


mohamedr002{at}e​.ntu​.ed​.sg

Computer Science and Engineering


Nanyang Technological University