2016.11-present: Lecturer, School of Mathematics and Physics, University of Science and Technology Beijing (USTB), China; 2014. 06-2016. 10: Postdoctor, School of mathematics and systems science, Beijing University of Aeronautics and Astronautics, China; 2009. 9-2014. 06: PhD, School of automation, University of Science and Technology Beijing (USTB), China;

1. Prove random constraint satisfaction problem (CSP) model RB has a clustering phase; find solution space of random CSP model d-k-CSP contains many widely distributed well-separated small clusters. Those explain why those models generate very hard instances. 2. Find a threshold phenomenon for pure random walk (PRW) on Model RB and give the threshold value; prove non-backtracking algorithm works in a range of parameters for Model RB. Those analyses of basic algorithms provides a reference for the design of algorithms.

1. Xu W , Gong F , Zhou G . Clustering phase of a general constraint satisfaction problem model d - k -CSP. Physica A: Statistical Mechanics and its Applications, 2019, 537:122708. 2. Xu Wei, Zhang Pan, Liu Tian, Gong Fuzhou. The solution space structure of random constraint satisfaction problems with growing domains. Journal of Statistical Mechanics: Theory and Experiment, 2015, P12006. 3. Xu Wei, Gong Fuzhou. Performances of Pure Random Walk Algorithms on Constraint Satisfaction Problems with Growing Domains. Journal of Combinatorial Optimization, 2016, 32(1):51-66