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SCSE PhD Student & A*STAR Scholar, Mohamed Ragab Finalist Paper Award at the 12th IEEE International Conference on Prognostics and Health Management (ICPHM2020)
Mohamed Ragab, SCSE’s PhD student & A*STAR scholar, clinched the Finalist Paper Award at 12th IEEE International Conference on Prognostics and Health Management (ICPHM2020). His paper, Adversarial Transfer Learning for Machine Remaining Useful Life Prediction, presented a novel adversarial transfer learning approach to predict the remaining useful life of industrial machines under different working conditions or different fault modes with no required labels.
The award is an important milestone in his PhD studies and is a reaffirmation of the relevance and potential of his research. Mohamed’s research focus on developing advanced deep learning techniques towards smart data-driven predictive maintenance. He would like to express his heartfelt gratitude to his PhD supervisor at NTU, Associate Professor Kwoh Chee Keong as well as his mentors at I2R, A*star including Dr Chen Zhenghua, Dr Wu Min, and Associate Professor Li Xiaoli.
The ICPHM 2020 is organized by IEEE Reliability society, it focuses on the condition monitoring applications for manufacturing industries. It attracts participants from highly reputed academic institutions and also from distinguished industrial companies such as Boeing, Hitachi, Toyota, General Motors, and NEC labs.” (http://scse.ntu.edu.sg/NewsnEvents/Pages/News-Detail.aspx?news=b9c2561f-b744-429c-a5fa-4fdcf7c0e597)
The award is an important milestone in his PhD studies and is a reaffirmation of the relevance and potential of his research. Mohamed’s research focus on developing advanced deep learning techniques towards smart data-driven predictive maintenance. He would like to express his heartfelt gratitude to his PhD supervisor at NTU, Associate Professor Kwoh Chee Keong as well as his mentors at I2R, A*star including Dr Chen Zhenghua, Dr Wu Min, and Associate Professor Li Xiaoli.
The ICPHM 2020 is organized by IEEE Reliability society, it focuses on the condition monitoring applications for manufacturing industries. It attracts participants from highly reputed academic institutions and also from distinguished industrial companies such as Boeing, Hitachi, Toyota, General Motors, and NEC labs.” (http://scse.ntu.edu.sg/NewsnEvents/Pages/News-Detail.aspx?news=b9c2561f-b744-429c-a5fa-4fdcf7c0e597)
