Russell, M., Wang, P., Liu, S., & Jawahir, I. S. (2022). Mixed-up experience replay for adaptive online condition monitoring. Manuscript submitted for publication.

Russell, M., Kershaw, J., Xia, Y., Lv, T., Li, Y., Ghassemi-Armaki, H., Carlson, B. E., & Wang, P. (2022). Comparison and explanation of data-driven modeling for weld quality prediction in resistance spot welding. Manuscript submitted for publication.

Russell, M., & Wang, P. (2022). Normalizing flows for intelligent manufacturing. Manuscript submitted for publication.

Russell, M., & Wang, P. (2022). Improved representations for continual learning of novel motor health conditions through few-shot prototypical networks. 2022 IEEE 18th Conference on Automation Science and Engineering (CASE), 1551–1556. Publisher

Wang, P., Kershaw, J., Russell, M., Zhang, J., Zhang, Y., & Gao, R. X. (2022). Data-driven process characterization and adaptive control in robotic arc welding. CIRP Annals 71(1), 45–48. Publisher

Wang, P., Russell, M., Kershaw, J., Xia, Y., Lv, T., Li, T., Ghassemi-Armaki, H., & Carlson, B. E. (2022). Interpretable data-driven prediction of resistance spot weld quality. 2022 International Symposium on Flexible Automation (ISFA).

Russell, M., & Wang, P. (2022). Physics-informed deep learning for signal compression and reconstruction of big data in industrial condition monitoring. Mechanical Systems and Signal Processing 168, 108709. Publisher


Russell, M. B., King, E. M., Parrish, C. A., & Wang, P. (2021). Stochastic modeling for tracking and prediction of gradual and transient battery performance degradation. Journal of Manufacturing Systems 59, 663–674. Publisher

Russell, M., Hong, P., Blakely, L., Kirkham, M., Enyoghasi, C., Wang, P., & Badurdeen, F. (2021). Smartphone app design for product use sustainability evaluation. EcoDesign 2021 International Symposium.


Russell, M., & Wang, P. (2020). Domain adversarial transfer learning for generalized tool wear prediction. Annual Conference of the PHM Society 12, 1–8. PDF

Russell, M., & Wang, P. (2020). Transferable deep learning for in-situ tool wear diagnosis. 2021 International Symposium on Flexible Automation (ISFA). Publisher


Russell, M., & Straub, J. (2017). Characterization of command software for an autonomous attitude determination and control system for spacecraft. International Journal of Computers and Applications 39(4), 198–209. Online

Hamlet, C., Straub, J., Russell, M., & Kerlin, S. (2017). An incremental and approximate local outlier probability algorithm for intrusion detection and its evaluation. Journal of Cybersecurity Technology 1(2), 75–87. Online

Matthew Russell

Written by Matthew Russell who follows Jesus and studies machine learning at the University of Kentucky. Get to know him or check out his projects on GitHub.