Journal Publications 

  1. Xu R., Wang C., Li, Y., and Wu J.* (2025). “Generalized Time Warping Invariant Dictionary Learning for Time Series Classification and Clustering,” IEEE Transactions on Pattern Analysis and Machine Intelligence, accepted.
  2. Michalek A.*, Villarini G., Andreas P., Done J., Johnson D., and Wang C. (2025). “Precipitation and temperature driven future changes to flooding in Alaska,” Geophysical Research Letters, accepted.
  3. Fallahdizcheh A., and Wang C.* (2024). “Variational Inference based transfer learning for profile monitoring with incompelte data,” IISE Transactions, accepted.
  4. Xia Z., Hu Z., He Q., and Wang C.* (2024). “Real-time transfer active learning for functional regression and prediction based on multi-output Gaussian process,” IEEE Transactions on Signal Processing, 72, 4163-4177.
  5. Wolf R., Jiang L., Alharbi K., Zhang P., Wang C., and Qin H.* (2024). “Heterogeneous transfer learning of electrohydrodynamic printing under zero-gracity towards in-sapce manufacturing,” Journal of Manufacturing Science and Engineering, 146 (12): 121002.
  6. Kim, T.*, Villarini, G., Done, J., Johnson, D., Prein, A., and Wang, C. (2024). “Dominant sources of uncertainty for downscaled climate: A military installation perspective,” Journal of Geophysical Research: Atmospheres, 129 (12), e2024JD040935.
  7. Zan X., Semenov A.*, Wang C., Xian, X., and Geremew W. (2024). “Causality-aware social recommender system with network homophily informed multi-treatment confounders,” Information Sciences, 676, 120729.
  8. Yao J., Balasubramaniam B., Li, B., Kreiger, E., and Wang C.* (2024). “Adaptive sampling and monitoring of partially observed images”, Journal of Quality Technology, 56 (2), 157-173.
  9. Hu Z., Wang C., Wu J., and Du D.* (2024). “Gaussian process latent variable model-based multi-output modeling of incomplete data”, IEEE Transactions on Automation Science and Engineering, 21 (2), 1941-1951.
  10. Yao J., Xian X., and Wang C.* (2023). “Adaptive sampling for monitoring multi-profile data with within-and-between profile correlation”, Technometrics, 65 (3), 375-387.
  11. Fallahdizcheh A., Laroia S., and Wang C.* (2023). "Sequential active contour based on morphological-driven thresholding for ultrasound image segmentation of ascites," IEEE Journal of Biomedical and Health Informatics, 27 (9), 4305-4316.
  12. Zhang, J., Wang, C., Li, J., Xie, Y., Mao, L.*, and Hu, Z.* (2023). A Bayesian method for capacity degradation prediction of lithium-ion battery considering both within and cross group heterogeneity. Applied Energy, 351, 121855.
  13. Fallahdizcheh A., and Wang C.* (2023). "Data-level transfer learning for degradation modeling and prognosis," Journal of Quality Technology, 55 (2), 140-162.
  14. Wang X., Wang C.*, Song X., Kirby L., and Wu J.* (2023). "Regularized multi-output Gaussian convolution process with domain adaptation", IEEE Transactions on Pattern Analysis and Machine Intelligence, 45 (5), 6142-6156.
  15. Fallahdizcheh A., and Wang C.* (2022). "Transfer learning of degradation modeling and prognosis based on multivariate functional analysis with heterogeneous sampling rates," Reliability Engineering & System Safety, 223: 108448.
  16. McGehee D.*, Cheryl A., Kasarla P., and Wang C. (2022). "Quantifying and recommending seat belt reminder timing using naturalistic driving video data," Journal of Safety Research, 80: 399-407.
  17. Ellis D.*, Tatum M., Wang C., Thomas G., and Peters T. (2022). "Combining physics-based and Kriging models to improve the estimation of noise exposure," Journal of Occupational and Environmental Hygiene, 19 (6), 343-352.
  18. Fallahdizcheh A., and Wang C.* (2022). “Profile monitoring based on transfer learning of multiple profiles with incomplete samples,” IISE Transactions, 54 (7), 643-658.
  19. Lee J., Wang C., Sui X., Zhou S.*, and Chen J. (2022). “Landmark-embedded Gaussian process with applications for functional data modeling”, IISE Transactions, 54 (11), 1033-1046.
  20. Hu Z., and Wang C.* (2022). “Nonlinear online multi-output Gaussian process for multi-stream data informatics,” IEEE Transactions on Industrial Informatics, 18 (6), 3885-3893.
  21. Gao Y., Huang X., Wang C., and Wu J.* (2022). “Estimating size and number density of three-dimensional particles using truncated cross-sectional data,” Journal of Manufacturing Science and Engineering, 144 (2): 021002.
  22. Kasarla P., Wang C.*, Brown T., and McGehee D. (2021) “Modeling and prediction of driving performance measures based on multi-output convolutional Gaussian process,” Accident Analysis & Prevention, 161: 106360.
  23. Wang C., Pu H., Sui X., Zhou S.*, and Chen J. (2021), “Hybrid modeling and sensitivity analysis on reduced graphene oxided filed-effect transistor”, IEEE Transactions on Nanotechnology, 20: 404-416.
  24. Wang C., Zhang W., and Villarini G.* (2021). “On the use of convolutional Gaussian process to improve the seasonal forecasting of precipitation and temperature”, Journal of Hydrology, 593: 125862.
  25. Wang C.*, and Zhou S. (2021). “Control of key performance indicators of manufacturing production systems through pair-copula modeling and stochastic optimization”, Journal of Manufacturing Systems, 58: 120-130.
  26. Wang C., Zhu X., Zhou S.*, and Zhou Y. (2021). “Bayesian learning of structures of ordered block graphical models with an application on multistage manufacturing processes”, IISE Transactions, 53 (7), 770-786.
  27. Wang C., and Zhou S.* (2019). “Approximate Key Performance Indicator Joint Distribution through Ordered Block Model and Pair Copula Construction”, IISE Transactions, 51 (11),1265-1278.
  28. Wang C., and Zhou S.* (2018). “Process Tracking and Monitoring Based on Discrete Jumping Model”. Journal of Quality Technology, 50 (1): 34-48.
  29. Wang C., and Zhou S.* (2017). “Contamination Source Identification Based on Sequential Bayesian Approach for Water Distribution Network with Stochastic Demands”. IISE Transactions, 49 (9): 899-910.
  30. Zhu J., Wang C., Hu Z., Kong F.*, and Liu X. (2017). “Adaptive Variational Mode Decomposition Based on Artificial Fish Swarm Algorithm for Fault Diagnosis of Rolling Bearings”. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 231 (4): 635-654.
  31. Hu Z., Wang C., Zhu J., Liu X., and Kong F.* (2016). “Bearing Fault Diagnosis Based on an Improved Morphological Filter”. Measurement, 80 (0): 163-178.
  32. Wang C., Shen C., He Q.*, Zhang A., Liu F., and Kong F. (2016). “Wayside Acoustic Defective Bearing Detection Based on Improved Dopplerlet Transform and Doppler Transient Matching”. Applied Acoustics, 101 (1): 141-155.
  33. Wang C., Hu F., He Q.*, Zhang A., Liu F., and Kong F. (2014). “De-noising of Wayside Acoustic Signal from Train Bearings Based on Variable Digital Filtering”. Applied Acoustics, 83 (1): 127- 140.
  34. Wang C., Kong F., He Q.*, Hu F., and Liu F. (2014). “Doppler Effect Removal Based on Instantaneous Frequency Estimation and Time Domain Re-sampling for Wayside Acoustic Defective Bearing Detector System”, Measurement, 50 (0): 346-355.