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中南大学数学与统计学院教授 (full professor),博士生导师,中南大学和德国法兰克福大学联合培养博士,研究兴趣为随机微分方程数值方法、生成式AI中的扩散模型 (diffusion model)和抽样算法的数学理论、计算金融 (computational finance)、Langevin Monte Carlo (LMC)、Multilevel Monte Carlo (MLMC)等。在上述研究领域取得一系列创新成果,论文发表在SIAM Journal on Numerical Analysis、Mathematics of Computation、SIAM Journal on Scientific Computing、IMA Journal of Numerical Analysis、BIT Numerical Mathematics、Journal of Scientific Computing、Advances in Computational Mathematics、Stochastic Processes and their Applications 等计算数学或概率论相关领域的权威刊物。系列研究成果获得来自美国、英国、德国、瑞士、法国、瑞典等众多国家的课题组的持续跟进、引用和好评,引用的刊物包括Memoirs of AMS、Ann Probab、Probab Theory Related Fields、Ann Appl Probab、Transactions of AMS、J. Math. Pures Appl.、Stoch Proc Appl、Numerische Mathematik、SIAM J Numer Anal、SIAM Sci Comput、Math Comp、Found Comput Math等。自2015年起受邀担任《Math Review》评论员,长期担任SIAM Journal on Numerical Analysis、Numerische Mathematik、Mathematics of Computation、SIAM Journal on Scientific Computing、IMA Journal of Numerical Analysis、Annals of Probability等计算数学或概率论权威刊物审稿人。现主持2项国家自然科学基金面上项目。已主持完成1项国家自然科学基金面上项目、1项湖南省杰出青年基金项目、1项国家自然科学基金青年项目、1项湖南省自然科学基金青年项目、2015年第二批“中南大学升华育英”人才计划项目、中南大学第五批创新驱动计划项目、1项中国博士后科学基金特别资助项目及1项中国博士后科学基金面上项目。本人学术交流广泛,多次应邀访问瑞士联邦理工学院(ETH)、中科院数学与系统科学研究院等国内外著名高校或研究所,多次应邀参加国际学术会议并做会议特邀报告或大会专题邀请报告。特别地,两次受邀参加世界著名数学研究所——Mittag-Leffler研究所举办的随机偏微分方程数值方法国际研讨会并做会议特邀报告。与多名国际著名的随机微分方程数值分析专家(如Peter Kloeden教授、Stig Larsson教授、Arnulf Jentzen教授、Sotirios Sabanis教授、Gabriel Lord教授、David Cohen教授、Charles-Edouard Brehier教授、Andreas Neuenkirch教授、Raphael Kruse教授等)保持广泛而紧密的学术交流与合作。欢迎数学基础好、有志于做学术研究的同学,特别是有保研资格的优秀本科生加盟课题组。
4. 国家自然科学基金面上项目 “随机微分方程的长时间数值逼近及相关问题研究”,No.12471394, 2025.01-2028.12(主持) 3. 国家自然科学基金面上项目 “局部单调性条件下的随机微分方程数值方法研究”,No.12071488, 2021.01-2024.12(主持) 2. 国家自然科学基金面上项目 “分布依赖随机微分方程数值算法研究 ”,No.12371417, 2024.01-2027.12(参加,排名第2) 1. 国家自然科学基金面上项目 “系数不连续的随机微分方程及其数值分析”,No.11971488, 2020.01-2023.12(参加,排名第2)
12. 湖南省杰出青年基金项目“随机发展方程的数值解法”,No. 2020JJ2040, 2020.01-2022.12 (主持) 11. 国家自然科学基金面上项目 “两类随机发展方程的数值分析”,No.11671405, 2017.01-2020.12(主持) - 2022年度湖南省自然科学奖二等奖(第一完成人)“随机微分方程数值算法及其理论分析” - 2014年湖南省优秀博士学位论文 - 2016年度中国仿真学会优秀论文奖 -10th International Congress on Industrial and Applied Mathematics (ICIAM 2023 Tokyo), Waseda University, Tokyo, Japan August 20-25, 2023 (invited talk in the mini-symposium "Numerical methods for stochastic partial differential equations") -2019 IMS China, Dalian, July 6-10, 2019 (invited talk in an invited mini-symposium) -Advances in Numerics for S(P)DEs, Gothenburg, Sweden, Oct. 14-18, 2024. ********** Recently published papers ********** 13. Chenxu Pang, Xiaojie Wang, Antithetic multilevel Monte Carlo method for approximations of SDEs with non-globally Lipschitz continuous coefficients, Stochastic Processes and their Applications, 178: 104467, 2024. 12. Ruishu Liu, Andreas Neuenkirch and Xiaojie Wang, A strong order 1.5 boundary preserving discretization scheme for scalar SDEs defined in a domain, to appear in Mathematics of Computation, DOI: https://doi.org/10.1090/mcom/4014 (在线发表), 2024. 11. Mengchao Wang, Xiaojie Wang: A linearly implicit finite element full discretization scheme for SPDEs with non-globally Lipschitz coefficients, IMA Journal of Numerical Analysis (2024), DOI: 10.1093/imanum/drae012 (在线发表). 10. Xiaojie Wang, Yuying Zhao and Zhongqiang Zhang: Weak error analysis for strong approximation schemes of SDEs with super-linear coefficients, IMA Journal of Numerical Analysis (2023), DOI: 10.1093/imanum/drad083 (在线发表). 9. Xiaojie Wang: Mean-square convergence rates of implicit Milstein type methods for SDEs with non-Lipschitz coefficients, Advances in Computational Mathematics (2023) 49:37.
8. Meng Cai, Ruisheng Qi, Xiaojie Wang: Strong convergence rates of an explicit scheme for stochastic Cahn-Hilliard equation with additive noise, BIT Numerical Mathematics (2023) 63:43. 7. Chenxu Pang, Xiaojie Wang, Yue Wu: Linear implicit approximations of invariant measures of semi-linear SDEs with non-globally Lipschitz coefficients, Journal of Complexity, 83 (2024), Paper No. 101842. 6. Ruishu Liu, Xiaojie Wang, Lei Dai, An unconditional boundary and dynamics preserving scheme for the stochastic epidemic model, Calcolo, 61 (3): 1-29, 2024. 5. Yuying Zhao, Xiaojie Wang: Weak approximation schemes for SDEs with super-linearly growing coefficients, Applied Numerical Mathematics, 198: 176-191, 2024. 4. Meng Cai, Siqing Gan, Xiaojie Wang: Weak approximations of stochastic partial differential equations with fractional noise, Journal of Computational Mathematics 42(3), 735-754, 2024. 3. Ruishu Liu, Yulin Cao, Xiaojie Wang: Unconditionally positivity preserving explicit Euler-type schemes for a generalized Ait-Sahalia model, Numerical Algorithms (2024), DOI: 10.1007/s11075-024-01810-2 (在线发表). 2. Yingsong Jiang, Ruishu Liu, Xiaojie Wang, Jinghua Zhuo, Unconditionally positivity-preserving approximations of the Ait-Sahalia type model: Explicit Milstein-type schemes, Numerical Algorithms (2024), DOI: 10.1007/s11075-024-01861-5, (在线发表). 1. Ruisheng Qi, Meng Cai, Xiaojie Wang: Strong convergence rates of a fully discrete scheme for the stochastic Cahn-Hilliard equation with additive noise, Communications in Mathematical Sciences, 22(5), 1307-1346, 2024.
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