吴奖伦 - 北京师范大学-香港浸会大学

个人简介

吴奖伦教授于1991年获得中国科学院应用数学研究所博士学位。曾任武汉大学博士后（1991-1993）、中国科学院应用数学研究所副研究员（1993-1999）、德国波鸿-鲁尔大学洪堡学者（1993-1995）、DFG研究员及数学系助教（1996-2000）。2001年1月至2023年5月历任英国斯旺西大学讲师（2001）、高级讲师（2005）、Reader（2007）及终身教授（personal chair，2011）。曾担任斯旺西大学理学院国际事务代表（chief representative）及数学系金融数学专业本科和硕士专业主管（BSc & MSc director）。2023年6月加盟UIC。他曾兼任西北工业大学客座讲座教授（2019-2022）、陕西省“百人计划”特聘教授（西北大学，2013-2018）、华中科技大学数学中心客座教授（2014-2017）等。担任多个国际数学及应用数学杂志的编委。长期担任英国工程与物理科学基金会（EPSRC）、皇家学会（Royal Society）、香港研究资助局、意大利数学与计算机科学国家研究委员会评审。曾获德国DFG研究基金、伦敦数学会基金及英国EPSRC等资助。吴奖伦教授的主要研究领域为随机分析与随机偏微分方程、流体力学随机计算和模拟、随机动态数据处理分析、非标准无穷小分析和无穷维泛函分析。研究问题包括数理金融学、特殊结构量子场、统计力学和流体力学等学科中与概率论相关的无穷维分析及随机偏微分方程问题。发表SCI学术论文120余篇。吴奖伦教授已经指导随机分析及金融数学研究方向10余名博士研究生和40余名硕士研究生。奖励与荣誉德国洪堡学者 (1993-1995) 陕西省百人计划海外特聘教授（2013-2018）

研究领域

随机分析与随机偏微分方程、流体力学随机计算和模拟、随机动态数据处理分析、非标准无穷小分析和无穷维泛函分析

近期论文

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Dong, Zhao; Guo, Boling; Wu, Jiang-Lun; Zhou, Guoli: Global Well- Posedness and Regularity of Stochastic 3D Burgers Equation with Multiplicative Noise. SIAM J. Math. Anal. 55 (2023), no. 3, 1847-1882. Wang, Lidan; Wu, Jiang-Lun; Zhou, Guoli: Global well-posedness of stochastic nematic liquid crystals with random initial and boundary conditions driven by multiplicative noise. Appl. Math. Optim. 87 (2023), no. 1, Paper No. 5, 46 pages. Lv, Guangying; Gao, Hongjun; Wei, Jinlong; Wu, Jiang-Lun: On the Campanato and H?lder regularity of local and nonlocal stochastic di!usion equations. Discrete Contin. Dyn. Syst. Ser. B 28 (2023), no. 2, 1244-1266. Yin, Xiuwei; Wu, Jiang-Lun; Shen, Guangjun: Well-posedness for stochastic fractional Navier-Stokes equation in the critical Fourier-Besov space. J. Theoret. Probab. 35 (2022), no. 4, 2940-2959. Qiao, Huijie; Wu, Jiang-Lun: Path independence of the additive functionals for stochastic di!erential equations driven by G-Lévy processes. Probab. Uncertain. Quant. Risk 7 (2022), no. 2, 101-118. Shen, Guangjun; Xiang, Jie; Wu, Jiang-Lun: Averaging principle for distribution dependent stochastic di!erential equations driven by fractional Brownian motion and standard Brownian motion. J. Differential Equations 321 (2022), 381-414. Ren, Panpan; Wu, Jiang-Lun: Least squares estimation for path- distribution dependent stochastic di!erential equations. Appl. Math. Comput. 410 (2021), Paper No. 126457, 18 pages. Fan, Xiliang; Wu, Jiang-Lun Density estimates for the solutions of backward stochastic di!erential equations driven by Gaussian processes. Potential Anal. 54 (2021), no. 3, 483-501. Dong, Zhao; Wu, Jiang-Lun; Zhang, Rangrang; Zhang, Tusheng Large deviation principles for first-order scalar conservation laws with stochastic forcing. Ann. Appl. Probab. 30 (2020), no. 1, 324-367. Zhang, Rangrang; Zhou, Guoli; Guo, Boling; Wu, Jianglun: Global well-posedness and large deviations for 3D stochastic Burgers equations. Z. Angew. Math. Phys. 71 (2020), no. 1, Paper No. 30, 31 pp. Song, Jiao; Wu, Jiang-Lun A detection algorithm for the first jump time in sample trajectories of jump-di!usions driven by alpha-stable white noise. Comm. Statist. Theory Methods 48 (2019), no. 19, 4888-4902. Lv, Guangying; Gao, Hongjun; Wei, Jinlong; Wu, Jiang-Lun: BMO and Morrey-Campanato estimates for stochastic convolutions and Schauder estimates for stochastic parabolic equations. J. Differential Equations 266 (2019), no. 5, 2666-2717. Zou, Guang-an; Lv, Guangying; Wu, Jiang-Lun: Stochastic Navier-Stokes equations with Caputo derivative driven by fractional noises. J. Math. Anal. Appl. 461 (2018), no. 1, 595-609. Xu, Yong; Pei, Bin; Wu, Jiang-Lun: Stochastic averaging principle for di!erential equations with non-Lipschitz coe"cients driven by fractional Brownian motion. Stoch. Dyn. 17 (2017), no. 2, 1750013, 16 pages. Lv, Guangying; Wu, Jiang-Lun: Renormalized entropy solutions of stochastic scalar conservation laws with boundary condition. J. Funct. Anal. 271 (2016), no. 8, 2308-2338.