• 2012–2015, PhD in Applied and Computational Mathematics, University of Edinburgh, Edinburgh, United Kingdom (Advisor: Professor Benedict Leimkuhler, FRSE)

• Numerical Methods and Error Analysis for Stochastic Differential Equations
• Molecular Dynamics, Statistical Mechanics, Multiscale Methods
• Momentum-Conserving Thermostats, Dissipative Particle Dynamics
• Nonequilibrium Modelling, Adaptive Thermostats
• Bayesian Sampling, Machine Learning, Data Science

1. B. Leimkuhler and X. Shang. On the numerical treatment of dissipative particle dynamics and related systems. Journal of Computational Physics, 280, 72–95, (2015)
2. B. Leimkuhler and X. Shang. Adaptive thermostats for noisy gradient systems. SIAM Journal on Scientific Computing, 38, A712–A736, (2016)
3. X. Shang, Z. Zhu, B. Leimkuhler and A. Storkey. Covariance-controlled adaptive Langevin thermostat for large-scale Bayesian sampling. Advances in Neural Information Processing Systems (NIPS) 28, 37–45, (2015)
4. B. Leimkuhler and X. Shang. Pairwise adaptive thermostats for improved accuracy and stability in dissipative particle dynamics. Journal of Computational Physics, 324, 174–193, (2016)

Reviewer of

• Journal of Computational Physics
• Journal of Computational Chemistry