Peng Su

Publications as Main Authors:

Su, P.,Yuan H., Lu, Z., Chen, D. (2024). Integrating Self-Organizing Map and Graph Neural Networks to Detect Anomalies in Time-series Data. IEEE Sensors Journal.

Su, P., Chen, D. (2024). Adopting Graph Neural Networks to Analyze Human–Object Interactions for Inferring Activities of Daily Living.Sensors ,24, 2567

Su, P., Lu, Z., & Chen, D. (2023). Combining Self-Organizing Map with Reinforcement Learning for Multivariate Time Series Anomaly Detection. Proceedings 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC). October 1-4, 2023, Honolulu, Oahu, Hawaii, USA

Su, P.,Warg, F., & Chen, D. (2023). A Simulation-Aided Approach to Safety Analysis of Learning-Enabled Components in Automated Driving Systems. InProceedings of theIEEE 26th International Conference on Intelligent Transportation Systems (ITSC) 24th September–28th September.

Su, P., Kang, S., Tahmasebi, K. N., & Chen, D. (2023). Enhancing Safety Assurance for Automated Driving Systems by Supporting Operation Simulation and Data Analysis. InProceedings of the 33rd European Conference On Safety And Reliability (ESREL) 3rd September–8th September(pp. 249-255)

Su, P., Fan, T., & Chen, D. (2023, July). Scheduling Resources to Deploy Monitors in Automated Driving Systems. InInternational Conference on Dependability and Complex Systems (DepCOS). Cham: Springer Nature Switzerland (pp. 285-294).

Su, P., Zhu, Z., Zhong, S., Huang, J., Ottikkutti, S., Tahmasebi, K. N., ... & Chen, D. (2023). Using a VAE-SOM architecture for anomaly detection of flexible sensors in limb prosthesis.Journal of Industrial Information Integration,35, 100490.

Su, P., & Chen, D. (2022, May). Using fault injection for the training of functions to detect soft errors of dnns in automotive vehicles. InInternational Conference on Dependability and Complex Systems (DepCOS). Cham: Springer International Publishing (pp. 308-318).

Publications as Co-Authors:

Huang, J., Zhu, Z.,Su, P., Chen, D., Zheng, L. R., & Zou, Z. (2024). A Reconfigurable Near-Sensor Processor for Anomaly Detection in Limb Prostheses.IEEE Transactions on Biomedical Circuits and Systems.

Kang, S., Guo, H.,Su, P., Zhang, L., Liu, G., Xue, Y., & Wu, Y. (2023, October). Ecsas: Exploring critical scenarios from action sequence in autonomous driving. In2023 IEEE 32nd Asian Test Symposium (ATS) (pp. 1-6). IEEE Computer Society.

Chen, D.,Su, P., Ottikkutti, S., Vartholomeos, P., Tahmasebi, K. N., & Karamousadakis, M. (2022). Analyzing Dynamic Operational Conditions of Limb Prosthetic Sockets with a Mechatronics-Twin Framework.Applied Sciences,12(3), 986.