Tianfang Xu


Research Interests

Numerical simulation and uncertainty quantification of groundwater flow and solute transport

Water resources sustainability

Coupled climate, hydrologic and social-economic systems

Model-data fusion

Machine learning



Ph.D. Civil Engineering, University of Illinois at Urbana-Champaign, Jun. 2012 – Aug. 2016

Thesis title: An efficient fully Bayesian approach to uncertainty quantification of groundwater models

M.S. Civil Engineering, University of Illinois at Urbana-Champaign, Aug. 2010 – May. 2012

Thesis title: Use of data-driven models to improve prediction of physically based groundwater models.

B.S. Geotechnical Engineering, Nanjing University, China, Sep. 2006 – Jun. 2010



Xu, A. J. Valocchi, M. Ye and F. Liang. Quantifying model structural error: efficient Bayesian calibration of a regional groundwater flow model with a data-driven error model and fast surrogates. Water Resources Research, submitted.

Xu and K. Guan, Temporally and spatially ranging response of rainfed corn yield to climate and extreme events in the U.S. Corn Belt, Global Change Biology, in preparation.

Xu, A. J. Valocchi, M. Ye, F. Liang and Y.F. Lin. Bayesian calibration of groundwater models with input data uncertainty. Water Resources Research, in revision.

Xu and A. J. Valocchi. A Bayesian approach to improved calibration and prediction of groundwater models with structural error. Water Resources Research, 51(11): 9290-9311, 2015.

Xu and A. J. Valocchi. Data-driven methods to improve baseflow prediction of a regional groundwater model. Computers & Geosciences, 85(B): 124-136, 2015.

Choi, J., E. Amir, T. Xu and A. J. Valocchi. Learning relational Kalman filtering. In Proc. 29th AAAI Conf. on Artificial Intelligence (AAAI-15), Austin, TX, Jan. 2015.

T. Xu, A. J. Valocchi, J. Choi, and E. Amir. Use of machine learning methods to reduce predictive error of groundwater models. Groundwater, 52(3): 448-460, 2014.

Complete CV

CV (Last Updated September 2016)