1. Ke, Y. T., Cheng, C. C., Lin, Y. C., Ni, Y. Q., Hsu, K. T., & Wai, T. T. (2020). Preliminary study on assessing delaminated cracks in cement asphalt mortar layer of high-speed rail track using traditional and normalized impact– echo methods. Sensors (Switzerland), 20(11), [3022]. 
  2. Wan, H. P., & Ni, Y. Q. (2020). A New Approach for Interval Dynamic Analysis of Train-Bridge System Based on Bayesian Optimization. Journal of Engineering Mechanics, 146(5), [04020029]. 
  3. Wang, Y. W., Ni, Y. Q., & Wang, X. (2020). Real-time defect detection of high-speed train wheels by using Bayesian forecasting and dynamic model. Mechanical Systems and Signal Processing, 139, [106654]. 
  4. Ding, S., Wang, Y. W., Ni, Y. Q., & Han, B. (2020). Structural modal identification and health monitoring of building structures using self-sensing cementitious composites. Smart Materials and Structures, 29(5), [055013]. 
  5. Zhou, H. F., Lu, L. J., Li, Z. Y., & Ni, Y. Q. (2020). Exploration of temperature effect on videogrammetric technique for displacement monitoringSmart Structures and Systems25(2), 135-153.
  6. Ni, Y. Q., & Zhang, Q. H. (Accepted/In press). A Bayesian machine learning approach for online detection of railway wheel defects using track-side monitoring. Structural Health Monitoring.
  7. Wang, Y. W., & Ni, Y. Q. (Accepted/In press). Bayesian dynamic forecasting of structural strain response using structural health monitoring data. Structural Control and Health Monitoring
  8. Ying, Z. G., & Ni, Y. Q. (2020). A multimode perturbation method for frequency response analysis of nonlinearly vibrational beams with periodic parameters. Journal of Vibration and Control, 26(13-14), 1260-1272. 
  9. Zhang, Q., & Ni, Y. Q. (2020). Improved Most Likely Heteroscedastic Gaussian Process Regression via Bayesian Residual Moment Estimator. IEEE Transactions on Signal Processing, 68, 3450-3460.