Dr Xiang Zhou received his BSc from Peking University (School of Mathematical Sciences) and PhD from Princeton University (PACM). Before joining City University in 2012, he worked as a research associate at Princeton University and Brown University. His major research focus is the study of rare event and the development of new computational methods for stochastic models and machine learning algorithms. His research interests include the transitions in nonlinear stochastic dynamical systems, stochastic simulation, transition-state/saddle-point calculations and the exploration of high dimensional non-convex energy landscapes. His research results have turned into peer-reviewed papers in SIAM journals, Journal of Computational Physics, Chaos, Nonlinearity and Annals of Applied Probability, etc.
He has a joint appointment at Department of Mathematics, College of Science, but recuites PhD students only via School of Data Science.
Previous Experience
- May 2012 - Jun 2018, Assistant Professor, Department of Mathematics, City University of Hong Kong.
Journal
- (May 2020). Stochastic dynamics of an active particle escaping from a potential well. Chaos. 30. 053133 doi:10.1063/1.5140853
- (June 2019). Quasi-potential calculation and minimum action method for limit cycle. Journal of Nonlinear Science. 29. 961 - 991. doi:10.1007/s00332-018-9509-3
- (March 2016). Iterative minimization algorithm for efficient calculations of transition states. Journal of Computational Physics. 309. 69 - 87. doi:10.1016/j.jcp.2015.12.056
- (January 2015). A cross-entropy scheme for mixtures. ACM Transactions on Modeling and Computer Simulation. 25. doi:10.1145/2685030
- (June 2011). The gentlest ascent dynamics. Nonlinearity. 24. 1831 - 1842. doi:10.1088/0951-7715/24/6/008
Last update date :
08 Sep 2021
