Faculty
Education
Ph.D., Statistics (May, 1992), University of North Carolina at Chapel Hill. Dissertation: Stochastic differential equations in duals of nuclear spaces (G. Kallianpur, advisor)
M.A., Statistics (July, 1986), Peking University, Beijing, China. Dissertation: Some problems about diffusion processes (M.P. Qian, advisor)
B.S., Mathematics (July, 1983), Peking University, Beijing, China.
Employment history
Chair Professor, Southern University of Science and Technology, 2017-present.
Professor, University of Macau, 2012-2017.
Professor, University of Tennessee, 2004-2014.
Associate Professor, University of Tennessee, 1999-2004.
Assistant Professor, University of Tennessee, 1993-1999
Visiting Lecturer, University of North Carolina at Charlotte, 1992-1993.
Instructor, Peking University, 1986-1988
Research interests
Stochastic differential equations, Markov processes, Limit theory, Stochastic analysis, Stochastic control and filtering, Mathematical finance.
Awards received
Humboldt Research Fellowship, 2003.
Canada Research Chair in Stochastic Processes and Filtering. 2002.
University of Tennessee-Oak Ridge National Lab Science Alliance research award. 1996-2000.
Graduate School Dissertation Fellowship. 1992
George E. Nicholson, Jr. Fellowship, 1989.
Selected Publications
1.Jie Xiong (2013). Three Classes of Nonlinear Stochastic Partial Differential Equations. World Scientific.
2.J. Xiong (2008). An Introduction to Stochastic Filtering Theory, Oxford Graduate Texts in Mathematics. 18. Oxford University Press.
3.T. Hida, R. Karandikar, H. Kunita, B. Rajput, S. Watanabe and J. Xiong (editors). Stochastics in Finite and Infinite Dimensions: In Honor of Gopinath Kallianpur. pp. 500. Birkhauser, 2000.
4.G. Kallianpur and J. Xiong (1995). Stochastic Differential Equations on Infinite Dimensional Spaces, IMS Lecture notes-monograph series, Vol. 26.
5.R. Wang, J. Xiong and L. Xu (2017). Irreducibility of stochastic real Ginzburg-Landau equation driven by stable noises and applications. Bernoulli, 23, No. 2, 1179-1201.
6.Z. Dong, J. Xiong, J. L. Zhai and T. S. Zhang (2017), A Moderate Deviation Principle for 2-DStochastic Navier-Stokes Equations Driven by Multiplicative L′evy Noises. J. Funct. Anal., 272, no. 1, 227-254.
7.J. Xiong and X. Yang (2016) Superprocesses with interaction and immigration. Stochastic Processes Appl. 126, 3377-3401.
8.Y. Chen, H. Ge, J. Xiong and L. Xu (2016). The Large Deviation Principle and Fluctuation Theorem for the Entropy Product Rate of a Stochastic Process in Magnetic Fields. J. Math. Physics. 57, 073302
9.F. Wang, J. Xiong and L. Xu (2016). Asymptotics of Sample Entropy Production Rate for Stochastic Differential Equations. Journal Statistical Physics.163, no. 5, 1211-1234,
10.S. Lenhart, J. Xiong and J. Yong (2016). Optimal Controls for Stochastic Partial Differential Equations with an Application in Controlling Rabbit Population. SIAM Control. Optim. 54, no. 2, 495-535
11.J.T. Shi, G.C. Wang and J. Xiong (2016). Leader-Follower Stochastic Differential Game with Asymmetric Information and Applications. Automatica J. IFAC 63, 60-73.
12.G. Wang, Z. Wu and J. Xiong (2015). A linear-quadratic optimal control problem of forward-backward stochastic differential equations with partial information. IEEE Transactions on Automatic Control 60， No.11, 2904-2916.
13.P. Fatheddin and J. Xiong (2015). Large deviation principle for some measure-valued processes. Stoch. Proce. Appl. 125, no. 3, 970-993.
14.Zenghu Li, Huili Liu, Jie Xiong and Xiaowen Zhou (2013). The reversibility and an SPDE for the generalized Fleming-Viot processes with mutation. Stoch. Proce. Appl.123, 4129-4155.
15.J. Xiong (2013). Super-Brownian motion as the unique strong solution to a SPDE. Ann. Probab. 41, No. 2, 1030-1054.
16.G.C. Wang, Z. Wu and J. Xiong (2013). Maximum principles for optimal control of forward-backward stochastic systems under partial information. SIAM J. Control Optim. 51, No. 1, 491-524.
17.Z. Li, H. Wang, J. Xiong and X. Zhou (2012), Joint continuity of the solutions to a class of nonlinear SPDEs. Probab. Theory Relat. Fields 153, No. 3, 441-469.
18.J. Detemple, W. Tian and J. Xiong (2012). Optimal stopping with reward constraints. Financial Stochastics 16, 423-448.
19.L. Mytnik, J. Xiong and O. Zeitouni (2011). Snake representation of a superprocess in random environment. ALEA, Lat. Am. J. Probab. Math. Stat. 8, 335–377.
20.J. Huang, G. Wang and J. Xiong (2009). A Maximum Principle for Partial Information Backward Stochastic Control Problems with Applications. SIAM J. Control Optim.40, No. 4, 2106-2117.
21.K.J. Lee, C. Mueller and J. Xiong (2009). Some properties for superprocess over a stochastic flow. Ann. Inst. H. Poincar\’e Probab. Statist. 45, No. 2, 477-490.
22.J. Xiong and X.Y. Zhou (2007). Mean-Variance portfolio selection under partial information. SIAM J. Control Optim. 46, no. 1, 156–175.
23.Z. Li, H. Wang and J. Xiong. (2004). A degenerate stochastic partial differential equation for superprocesses with singular interaction. Probab. Th. Relat. Fields 130, 1-17.
24.J. Xiong (2004). A stochastic log-Laplace equation. Ann. Probab. 32, 2362-2388.
25.D. Dawson, A. Etheridge, K. Fleischmann, L. Mytnik, E. Perkins, and J. Xiong (2002). Mutually catalytic processes in the plane: Finite measure states. Ann. Probab. 30, no. 4, 1681–1762.
26.K. Fleischmann and J. Xiong (2001). A cyclically catalytic branching model, Annals of Probability, 2, 820-861.
27.T. Kurtz and J. Xiong (1999). Particle representations for a class of nonlinear SPDEs. Stochastic Processes and their Applications 83, 103-126.
28.G. Kallianpur and J. Xiong, Large deviation principle for a class of stochastic partial differential equations, Annals of Probability, 24, 1996, 320-345.
29.G. Kallianpur and J. Xiong, Diffusion approximation of stochastic differential equations driven by Poisson random measures, Annals of Applied Probability, 5, 1995, 493-517.
30.J. Xiong and M. P. Qian (1990). Construction and properties of coupled diffusion processes, Acta Math. Appl. Sinica, 13, 391-400 (in Chinese).