Doctoral Symposium
The following candidates have been selected to participate in the 2024 Doctoral Consortium. Summaries of presentations will be available as part of the conference proceedings. For more details on the application and selection process please visit the Call for Doctoral Symposium page, and for any questions please contact Doctoral Consortium chair, Dr Jamie Coble, jamie@utk.edu.
Doctoral Symposium Panelists
- Marcia Baptista, Unversidade Nove de Lisboa
- Meng Li, NOV Inc.
- Xinyu Du, General Motors
Note that the Doctoral Symposium Sessions are open to all conference registrants as audience.
Congratulations to the Selected Participants!
| Student Name | Title | University |
| Ark Ifeanyi | A Graph Neural Network Approach to System-Level Health Index and Remaining Useful Life Estimation | University of Tennessee |
| Priscila Silva | PHM-Based Modeling for Cyberattack Classifier Performance | University of Massachusetts Dartmouth |
| Raffael Theiler | Digital Twin Generalization with Meta and Geometric Deep Learning | Ecole Polytechnique federale de Lausanne |
| Yan Xue | Diagnostics and Prognostics with High Dimensional Spatial-Temporal Data: From Structures to Human Brains | Arizona State University |
| Zhen Li | Remaining Useful Life Prognostics of Rolling Element Bearings Based on State Estimation Technologies | KU Leuven |
| Weijun Xu | Novel Uncertainty-aware Methods for Remaining Useful Life Prediction of Complex Systems | Politecnico di Milano |
| Mohammad Badfar | Adaptable and Generic Methods for Monitoring and Prognostics of Energy Assets | Wayne State |
| Sanjoy Kumar Saha | A Two-Step Framework for Predictive Maintenance of Cryogenic Pumps in Semiconductor Manufacturing | University of Ulster |
| Mattia Zanotelli | System-level Prognostics and Health Management for Complex Industrial Systems: An Application to PressurizedWater Reactors | University of Tennessee |
| Racquel Knust Domingues | Development of a methodology for diagnosing faults in bearings operating under variable operating conditions based on self-supervised learning | Federal University of Santa Catarina |
| Jae Gyeong Choi | Multimodal sensor-to-machined surface image diffusion for defect detection in industrial processes | Ulsan National Institute of Science and Technology |