Publications

(2019). Gradient Boosted Models for Enhancing Fatigue Cracking Prediction in Mechanistic-Empirical Pavement Design Guide. Journal of Transportation Engineering, Part B: Pavements.

DOI

(2019). Investigating Impacts of Asphalt Mixture Properties on Pavement Performance Using LTPP Data through Random Forests. Construction and Building Materials.

(2019). Direct Shear Properties of Railway Ballast Mixed with Tire Derived Aggregates: Experimental and Numerical Investigations. Construction and Building Materials.

DOI

(2019). Neural Networks for Fatigue Cracking Prediction Using Outputs from Pavement Mechanistic-Empirical Design. International Journal of Pavement Engineering.

DOI

(2018). Use of Random Forests Regression for Predicting IRI of Asphalt Pavements. Construction and Building Materials.

DOI

(2018). Improving Accuracy of Rutting Prediction for Mechanistic-Empirical Pavement Design Guide with Deep Neural Networks. Construction and Building Materials.

DOI

(2018). Field Performance Evaluation of Asphalt Mixtures Containing High Percentage of RAP Using LTPP Data. Construction and Building Materials.

(2018). Development in Innovative Characterization, Modeling and Simulation of Pavements and Materials. International Journal of Pavement Engineering.

DOI

(2017). Local Calibration of the Fatigue Cracking Models in the Mechanistic-Empirical Pavement Design Guide for Tennessee. Road Materials and Pavement Design.

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(2016). Effectiveness Analyses of Flexible Pavement Preventive Maintenance Treatments with LTPP SPS-3 Experiment Data. Journal of Transportation Engineering.