Background and activities
- 06/2019 - present: PhD candidate, Department of Ocean Operations and Civil Engineering, NTNU Aalesund, Norway. Data mining of ship status for onboard supporting of maritime operations (Main supervisor: Houxiang Zhang, Co-supervisors: Guoyuan Li and Stian Skjong)
- 09/2016 - 06/2019: Deparatment of Architecture and Civil Engineering, Zhejiang University. Hangzhou, China. M.Sc.
- 09/2012 - 06/2016: Deparatment of Architecture and Civil Engineering, Zhejiang University. Hangzhou, China. B.Sc.
- 2019 - present: KPN, "Digital Twins for Vessel Life Cycle Service (TwinShip)".
- Prognostics and health management
- Machine learning
- Bayesian method
Scientific, academic and artistic work
- (2021) Fault Detection with LSTM-based Variational Autoencoder for Maritime Components. IEEE Sensors Journal.
- (2021) An Uncertainty-aware Hybrid Approach for Sea State Estimation Using Ship Motion Responses. IEEE Transactions on Industrial Informatics.
- (2021) A Deep Learning Approach to Detect and Isolate Thruster Failures for Dynamically Positioned Vessels Using Motion Data. IEEE Transactions on Instrumentation and Measurement. vol. 70.
- (2020) Online Fault Detection in Autonomous Ferries: Using fault-type in-dependent spectral anomaly detection. IEEE Transactions on Instrumentation and Measurement. vol. 69 (10).
- (2020) A Novel Channel and Temporal-wise Attention in Convolutional Networks for Multivariate Time Series Classification. IEEE Access. vol. 8.