孙晓斌，男，1986年9月出生于江苏无锡，江苏师范大学数学与统计学院副教授。2015年6月博士毕业于南开大学数学科学学院，师从谢颖超教授。
研究方向：随机分析及其应用，随机(偏)微分方程
Email：xbsun@jsnu.edu.cn
受教育经历：
2012/09-2015/06，南开大学，数学科学学院，概率论与数理统计专业，博士
2009/09-2012/06，江苏师范大学，数学科学学院，概率论与数理统计专业，硕士
2005/09–2009/06，徐州师范大学，数学科学学院，数学与应用数学(师范)，学士
工作经历:
2019/06至今，江苏师范大学，数学与统计学院，副教授
2015/07-2019/06，江苏师范大学，数学与统计学院，讲师
访学经历：
2018/08-2019/08, 访问比勒菲尔德大学，数学系 合作导师：Michael Röckner 教授
2018/05-2018/08, 访问澳门大学，科技学院 合作导师：徐礼虎 副教授
2015/06-2015/09, 访问澳门大学，科技学院 合作导师：徐礼虎 副教授
2013/07-2014/06, 访问美国堪萨斯大学，数学系 合作导师：David Nualart 教授
获奖情况：
2021年 江苏省高校“青蓝工程”优秀青年骨干教师
2021年 江苏省高校第七届数学基础课青年教师授课竞赛暨首届全国大学数学课程思政邀请赛 二等奖
主持科研项目：
1.江苏省高校自然科学研究面上项目"Lévy 噪声驱动的随机偏微分方程的遍历性" (16KJB110006, 2016.09-2018.08)
2.国家自然科学基金青年项目"带跳随机偏微分方程的遍历性及密度正则性" (11601196，2017.01-2019.12)
3.国家自然科学基金面上项目"多尺度随机微分方程的渐近行为"(12271219, 2023.01-2026.12)
已发表或接收论文：
1. Y. Li, X. Sun, and Y. Xie. Fokker-Planck equations and maximal dissipativity for Kolmogorov operators for SPDE driven by Levy noise. Potential Anal. 38(2), 38-396. (2013)
2. Y. Li, H. Lv, X. Sun, and Y. Xie. Exponential behaviour of stochastic 2D Navier-Stokes equations driven by Lévy noise. Chinese J. Appl. Probab. Statist. 29, no. 2, 151-166.(2013)
3. X. Sun and Y. Xie. Ergodicity of stochastic dissipative equations driven by α-stable process. Stoch. Anal. Appl. 32 (1), 61-76. (2014)
4. B. Hu, X. Sun and Y. Xie. The Kolmogorov operator and Fokker-Planck equation associated to a stochastic Burgers equation driven by Levy noise. Illinois J. Math. 58, no.1, 167-205. (2014)
5. 孙晓斌, 谢颖超. 分数 Brown 运动驱动带 Markov 切换的随机微分方程解的密度存在性. 中国科学: 数学, 第 45 卷, 第 5 期: 639-646. (2015)
6. Y. Hu, J. Huang, D. Nualart and X. Sun. Smoothness of the joint density for spatially homogeneous SPDEs. J. Math. Soc. Japan no.4, 1605-1630.(2015)
7. X. Sun and Y. Xie. Poincaré-type inequality and integration by parts formula for non-symmetrical dissipative stochastic systems driven by Lévy noise. J. Systems Sci. Math. Sci. 36, no. 2, 248-266. (2016)
8. X. Sun, Y. Xiao, L. Xu and J. Zhai. Uniform dimension results for a family of Markov processes. Bernoulli 24，no.4B， 3924-3951.(2018)
9. Z. Dong, X. Sun, H. Xiao and J. Zhai. Averaging principle for one dimensional stochastic Burgers equation. J. Differential Equations 265, no. 10, 4749-4797. (2018)
10. X. Sun and Y. Xie. Smooth densities for SDEs driven by subordinated Brownian motion with Markovian switching. Front. Math. China 13，no. 6, 1447-1467.(2018)
11. X. Sun，Y. Xie and L. Xu. Exponential mixing for SPDEs driven by highly degenerate Lévy noises.Illinois J. Math. 63, no. 1, 75–102.(2019)
12. Y. Hu, D. Nualart, X. Sun and Y. Xie. Smoothness of density for stochastic differential equations with Markovian switching. Discrete & Continuous Dynamical Systems-B 24, no. 8，3615-3631.(2019)
13. X. Sun and J. Zhai. Averaging principle for stochastic real Ginzburg-Landau equation driven by α-stable process. Commun. Pure Appl. Anal. 19, no. 3, 1291-1319. (2020)
14. X. Sun, L. Xie and Y. Xie. Derivative formula for the Feynman-Kac semigroup of SDEs driven by rotationally invariant
15. W. Liu, M. Röckner, X. Sun and Y. Xie. Averaging principle for slow-fast stochastic differential equations with time dependent locally Lipschitz coefficients. J. Differential Equations 268, 2910-2948.(2020)
16. Y. Chen, Y. Shi, X. Sun. Averaging principle for slow-fast stochastic Burgers equation driven by α-stable process. Appl. Math. Lett. 103, 106199.(2020)
17. X. Sun, L. Xie and Y. Xie. Pathwise uniqueness for a class of SPDEs driven by cylindrical α-stable processes. Potential Anal. 53, no. 2, 659–675. (2020)
18. J. Gao, S. Li, X. Sun and Y. Xie. Averaging principle for slow-fast stochastic 2D Navier Stokes equation driven by Lévy noise. Math. Methods Appl. Sci. 44, no 7, 5475-5500. (2021)
19. X. Sun, L. Xie and Y. Xie. Averaging principle for slow-fast stochastic partial differential equations with Hölder continuous coefficients. J. Differential Equations 270, 476-504. (2021)
20. M. Röckner, X. Sun and Y. Xie. Strong convergence order for slow-fast McKean-Vlasov stochastic differential equations. Ann.Inst.Henri Poincare Probab.Stat.57(1) 4745-4777.(2021)
21. X. Sun, R. Wang, L. Xu and X. Yang. Large deviation for two-time-scale stochastic burgers equation. Stochastics and Dynamics 21(5) 2150023. (2021)
22. X. Sun, L. Xie and Y. Xie. Strong and weak convergence rates for slow-fast stochastic differential equations driven by α-stable process. Bernoulli 28(1) 343-369 (2022)
23. B.Li, Y. Meng, X. Sun and T. Yang. Optimal strong convergence rate for a class of McKean–Vlasov SDEs with fast oscillating perturbation. Statistics & Probability Letters 191,109662 (2022)
24. X. Sun and Y. Xie. Orders of strong and weak averaging principle for multi-scale SPDEs driven by α-stable process. J. Differential Equations 351,194-242. (2023)
25. M. Kong, Y. Shi and X. Sun. Well-posedness and averaging principle of McKean-Vlasov SPDEs driven by cylindrical α-stable process.Stoch. Anal. Appl. 41(4),672-692.(2023)
26. W. Liu, M. Röckner, X. Sun and Y. Xie. Strong averaging principle for slow-fast stochastic partial differential equations with locally monotone coefficients. Appl. Math. Optim. 87(3) Paper No. 39, 31 pp (2023)
27. X. Sun, H. Xia, Y. Xie and X. Zhou. Strong averaging principle for a class of slow-fast singular SPDEs driven by α-stable process.Frontiers of Mathematics.18(3), 565-590.(2023)
28. Y. Liao, K. Liu, X. Sun and L. Wang. Strong convergence rate for slow-fast stochastic differential equations with Markovian switching. Discrete & Continuous Dynamical Systems-B 28(8) 4281-4292. (2023)
29. W. Hong,S. Li,W. Liu and X. Sun. Central Limit Type Theorem and Large Deviation Principle for Multi-Scale McKean-Vlasov SDEs. Probability Theory and Related Fields 187(1-2) 133-201.(2023)
30.J. Bao, X. Sun, J. Wang, Y. Xie. Quantitative estimates for Lévy driven SDEs with different drifts and applications.J. Differential Equations 398 182-217.(2024)
31.Y.Shi, X.Sun, L.Wang and Y. Xie. Asymptotic behavior for multi-scale SDEs with monotonicity coefficients driven by Lévy processes. Potential Anal. 61(1),111-152. (2024)
32. W. Hong, S. Li and X. Sun. Diffusion approximation for multi-scale McKean-Vlasov SDEs through different methods. J. Differential Equations 414, 405-454.(2025)
33. Y. Ge, X. Sun and Y. Xie. Optimal convergence rates in the averaging principle for slow-fast SPDEs driven by multiplicative noise. Commun. Math. Stat. (2024). https://doi.org/10.1007/s40304-023-00363-5
34. P. Gao and X. Sun. Optimal convergence order for multi-scale stochastic Burgers equation.Stoch PDE: Anal Comp (2024). https://doi.org/10.1007/s40072-024-00336-x