“学术讲座”课程报告报名、名单公示通知（2019级）
66、夏学期第八周讲座一
报告题目：Modeling complex time series with tensor techniques
报告信息来源：中国科学院数学与系统科学研究院
报告人 Speaker：李国栋(香港大学)
时间 Datetime：2023-06-13 16：30-18：00
地点 Venue：腾讯会议 ID：929-2139-6317
报告摘要 Abstract：
The tensor, as an extension of matrices, has recently gained significant attention from econometricians and statisticians,and the literature has witnessed two types of its applications.Firstly, the involvement of tensors can facilitate the development of new inference tools, which are impossible under the framework of matrices alone. Secondly, many big data come in the form of tensors. This talk will introduce several of my research studies on high-dimensional time series modeling using tensors, and I will also present two inference tools for tensor valued time series.
报告人简介：
李国栋，现任香港大学统计精算系教投授。本科和硕士毕业于北京大学数学学院，2007年于香港大学统计精算系获得统计学博士，随后在南洋理工大学任助理教授。主要研究方向包标计量经济，时间序列分析，分位数回归，高维统计数据分析和机器学习。李教授目前发表学术论文60余稿，其中20余稿发表在Journal of Econometrics，Econometric Theory和Journal of Business and Economic Statistics等计量经济学的顶级期刊、以及统计学4大顶级期刊和机器学习的3大顶级会议上。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/QGOStIQv
65、夏学期第七周讲座二
报告题目：Sharp pointwise convergence on the Schrödinger operator along one class of curves
报告信息来源：浙江大学数学科学学院官网
报告人 Speaker：曹桢斌（北京师范大学）
时间 Datetime：2023-06-08 09:00-11:00
地点 Venue：腾讯会议 ID：256787687
报告摘要 Abstract：
Almost everywhere convergence on the solution of Schrödinger equation is an important problem raised by Carleson, which was essentially solved by Du-Guth-Li and Du-Zhang. In this talk, we discuss pointwise convergence on the Schrödinger operator along one class of curves.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/uCLr4Gx3
64、夏学期第七周讲座一
报告题目：(Group) Symmetry: A designing principle of neural circuits in the brain?
报告信息来源：上海交通大学数学科学学院官网
报告人 Speaker：Wenhao Zhang (UT Southwestern Medical Center)
时间 Datetime：2023-06-06 10:00-11:00
地点 Venue：腾讯会议 ID：404115947 密码：412467
报告摘要 Abstract：
Equivariant representation is necessary for the brain and artificial perceptual systems to faithfully represent the stimulus under some (Lie) group transformations. However, it remains unknown how recurrent neural circuits in the brain represent the stimulus equivariantly, nor the neural representation of abstract group operators. The present study uses a one-dimensional (1D) translation group as an example to explore the general recurrent neural circuit mechanism of the equivariant stimulus representation. We found that a continuous attractor network (CAN), a canonical neural circuit model, self-consistently generates a continuous family of stationary population responses (attractors) that represents the stimulus equivariantly. Inspired by the Drosophila’s compass circuit, we found that the 1D translation operators can be represented by extra speed neurons besides the CAN, where speed neurons’ responses represent the moving speed (1D translation group parameter), and their feedback connections to the CAN represent the translation generator (Lie algebra). We demonstrated that the network responses are consistent with experimental data. Our model for the first time demonstrates how recurrent neural circuitry in the brain achieves equivariant stimulus representation.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/NcBVrnAE
63、夏学期第六周讲座四
报告题目：Noncommutative weakly dominated martingales
报告信息来源：复旦大学数学科学学院官网
报告人 Speaker：吴恋教授（中南大学）
时间 Datetime：2023-06-02 16:00-17:00
地点 Venue：腾讯会议 ID：594-861-274
报告摘要 Abstract：
Motivated by the results from the classical probability theory, we introduce the concept of weak domination in the context of noncommutative martingales. Then we establish the weak-type and strong-type estimates for noncommutative martingales and their weak dominations. The proof mainly relies on a new Gundy’s decomposition that is well-suited for weakly dominated martingales. We show as well the corresponding inequalities for the square functions of such martingales. These results strengthen recent works on noncommutative differentially martingales, which in turn, give rise to a new application in harmonic analysis: a weak-type estimate (and also a completely bounded version) for the directional Hilbert transform associated with a quantum tori.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/fAYBjO8e
62、夏学期第六周讲座三
报告题目：Decarbonization of large financial markets
报告信息来源：北京大学统计科学中心
报告人 Speaker：Peter Tankov (ENSAE)
时间 Datetime：2023-06-01 15:00开始
地点 Venue：Zoom ID：860-2575-8911, 密码:322067
报告摘要 Abstract：
We build a model of a financial market where a large number of firms determine their dynamic emission strategies under climate transition risk in the presence of both green-minded and neutral investors. The firms aim to achieve a trade-off between financial and environmental performance, while interacting through the stochastic discount factor, determined in equilibrium by the investors' allocations. We formalize the problem in the setting of mean-field games and prove the existence and uniqueness of a Nash equilibrium for firms. We then present a convergent numerical algorithm for computing this equilibrium and illustrate the impact of climate transition risk and the presence of green-minded investors on the market decarbonization dynamics and share prices. We show that uncertainty about future climate risks and policies leads to higher overall emissions and higher spreads between share prices of green and brown companies. This effect is partially reversed in the presence of environmentally concerned investors, whose impact on the cost of capital spurs companies to reduce emissions. However, if future climate policies are uncertain, even a large fraction of green-minded investors is unable to bring down the emission curve: clear and predictable climate policies are an essential ingredient to allow green investors to decarbonize the economy.
报告人简介：
Peter Tankov is professor of quantitative finance at ENSAE, the French national school for statistics and economic administration, having previously worked at Paris-Cite university and Ecole Polytechnique. He is a mathematician, specialist in applied probability and stochastic processes. His current research interests include quantitative finance, energy finance, and green and sustainable finance. Peter is the author of over 50 research articles on these and other topics and of the widely read book, Financial Modelling with Jump Processes. He is the recipient of the 2016 Best Young Researcher in Finance award of the Europlace Institute of Finance and the principal investigator of several national grants. Peter is the scientific director of the Green and Sustainable Finance Research Program at Louis Bachelier Institute and member of editorial boards of the main quantitative finance journals: Mathematical Finance and Finance and Stochastics.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/ypbduPFk
61、夏学期第六周讲座二
报告题目：The length of the longest increasing subsequence in the Brownian separable permutons
报告信息来源：复旦大学数学科学学院官网
报告人 Speaker：William Da Silva （University of Vienna ）
时间 Datetime：2023-05-30 16:00-17:00
地点 Venue：zoom ID：742-1732-1564, 密码: 60YmDH
报告摘要 Abstract：
The Brownian separable permutons are a family of universal limits of random constrained permutations, depending on some parameter p in (0,1). I will provide explicit polynomial bounds for the length of the longest increasing subsequence in the Brownian separable permutons, and present simulations suggesting that the lower bound is close to optimal for all p. The strategy relies on a connection to fragmentation processes that I will highlight in the talk. The talk is based on joint work with Jacopo Borga (Stanford University) and Ewain Gwynne (University of Chicago).
报名链接：https://form.zju.edu.cn/#/dform/genericForm/lZ2LS6cO
签到名单：无
60、夏学期第六周讲座一
报告题目：Family Index Theorem and Eta Form
报告信息来源：同济大学数学科学学院官网
报告人 Speaker：刘博教授（华东师范大学）
时间 Datetime：2023-05-30 10:05-11:05
地点 Venue：腾讯会议 ID：692-144-257
报告摘要 Abstract：
In this talk, we will discuss various generalizations of the Atiyah-Singer index theorem and introduce a comparison formula of equivariant eta forms. This is a joint work with Xiaonan Ma.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/4wCNWFbR
59、夏学期第五周讲座四
报告题目：Mathematical Foundation of Distributed Machine Learning
报告信息来源：复旦大学数学科学学院官网
报告人 Speaker：叶颀教授（华东师范大学）
时间 Datetime：2023-05-27 14:00-15:00
地点 Venue：腾讯会议 ID：668 261 449, 密码: 200433
报告摘要 Abstract：
In this talk, we study the whole theory of regularized learning for generalized data in Banach spaces including representer theorems, approximation theorems, and convergence theorems. Specially, we combine the data-driven and model-driven methods to introduce the new algorithms and theorems of the regularized learning. Usually the data-driven and model-driven methods are used to analyze the black-box and white-box models, respectively. With the same thought of the Tai Chi diagram, we use the discrete local information of multimodal data and multiscale models to construct the global approximate solutions by the regularized learning. The work of the regularized learning for generalized data provides another road to study the theory and algorithms of machine learning including: the interpretability in approximation theory, the nonconvexity and nonsmoothness in optimization theory, the generalization and overfitting in regularization theory. Moreover, based on the regularized learning, we will discuss the composite algorithms for hierarchical teaching and image registration of our current research projects of the big data analysis in education and medicine.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/e2bbxSvG
58、夏学期第五周讲座三
报告题目：限制性框架下Schrödinger算子的谱分析
报告信息来源：浙江大学数学科学学院官网
报告人 Speaker：苗长兴（北京应用物理和计算数学研究所）
时间 Datetime：2023-05-25 09:30-11:00
地点 Venue：腾讯会议 ID：970741100
报告摘要 Abstract：
研究Schrödinger算子对应的散射理论有两种途径,其一是基于迹定理的加权空间框架,形成了常用的经典研究方法; 其二基于超曲面或余维为k光滑流形上Stein-Tomas限制性定理,形成了在限制性框架下研究Schrödinger算子谱理论的现代方法。报告重点介绍限制性理论与极限吸收原理(LAP)、波算子的缠结性质、Agmon-Kato-Kuroda定理之间的内在联系,可能涉及Schrödinger算子对应的LAP，弯曲Fourier变换、Agmon-Hörmander临界空间方法、波算子的 有界性、Schrödinger算子对应的散射理论及其在数学物理中的应用.
报告人简介：
苗长兴, 北京应用物理与计算数学研究所研究员。曾荣获国家杰出青年基金、于敏数理科学奖、中国工程物理研究院杰出专家、中国工程物理研究院科技创新一等奖，是我国自己培养的在国际偏微分方程领域有影响的杰出数学家。近年来在国际一流的学术刊物(如：CPAM、CMP、ARMA、MZ、JFA、JMPA、SIAM、AIHP、CPDE、PLMS等)上发表论文一百余篇, 主要贡献表现在调和分析、非线性色散方程的散射理论与流体动力学方程的数学理论等研究领域，解决了若干个具有国际影响的数学问题，得到了著名数学家Kenig、 Constantin等国际同行的高度评价。先后出版了《调和分析及其在偏微分方程中的应用》、《偏微分方程的调和分析方法》、《非线性波动方程的现代方法》、《Littlewood-Paley理论及其在流体动力学方程中的应用》等五部专著。对国内这一核心数学领域的研究与发展起到了基础性的作用.所领导的科研团队被国际数学联盟前主席Kenig称为“国际偏微分方程研究领域最具活力与影响力的团队之一”。与此同时, 培养了一批年轻有为的数学才俊。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/iNIiKhiS
57、夏学期第五周讲座二
报告题目：Mathematical Foundation of Distributed Machine Learning
报告信息来源：复旦大学数学科学学院官网
报告人 Speaker：吴强 教授（Middle Tennessee State University）
时间 Datetime：2023-05-24 09:00-10:00
地点 Venue：腾讯会议 ID：979 137 738, 密码: 200433
报告摘要 Abstract：
Machine learning is a central component of data science. The successful applications of machine learning algorithms in practice usually motivate theoretical studies on their computational and mathematical properties, which help researchers and practitioners to better understand the algorithms, identify appropriate application domains, and set up hyperparameters to achieve the best performance. This, however, is only one side of the story. On the other side, theoretical studies can also in turn motivate new algorithms by addressing the limitations of existing algorithms. This usually improves the performance in some specific scenarios or broadens the application domains of existing algorithms. In this talk, I will present the mathematical foundations of the divide and conquer approach for distributed machine learning. We proved the minimax optimality of several distributed kernel regression approaches. Based on these studies, we designed a bias correction strategy to improve the performance of distributed kernel regression and a recentering regularization approach to make distributed learning applicable in the classification setting.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/5X38Jn7L
56、夏学期第五周讲座一
报告题目：Interplay between Statistics and Computation in Machine Learning
报告信息来源：复旦大学数学科学学院官网
报告人 Speaker：应益明 教授（Department of Mathematics and Statistics, SUNY Albany）
时间 Datetime：2023-05-23 09:00-10:00
地点 Venue：腾讯会议 ID：170 756 929, 密码: 200433
报告摘要 Abstract：
Stochastic gradient methods (SGMs) have become the workhorse of machine learning (ML) due to their incremental nature with a computationally cheap update. In this talk, I will first discuss the close interaction between statistical generalization and computational optimization for SGMs in the framework of statistical learning theory (SLT). The core concept for this study is algorithmic stability which characterizes how the output of an ML algorithm changes upon a small perturbation of the training data. Our theoretical studies have led to new insights into understanding the generalization of overparameterized neural networks trained by SGD. Then, I will describe how this interaction framework can be used to derive lower bounds for the convergence of existing methods in the task of maximizing the AUC score which further inspires a new direction for designing efficient AUC optimization algorithms. Finally, I will briefly talk about future research directions.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/sfFx6wcP
55、夏学期第四周讲座四
报告题目：Brezis-Van Schaftingen-Yung and Bourgain-Brezis-Mironescu Formulae in Ball Banach Function Spaces
报告信息来源：复旦大学数学科学学院官网
报告人 Speaker：袁文教授（北京师范大学）
时间 Datetime：2023-05-19 16:00-17:00
地点 Venue：腾讯会议ID:690-187-949
报告摘要 Abstract：
Let $X$ be a Ball Banach function space. In this talk, we first recall the Bourgain-Brezis-Mironescu and the Brezis-Van Schaftingen-Yung formulae related to of the Sobolev space $W^{1,1}(\mathbb{R}^n)$. Then, under some mild assumptions, and via a new method involving extrapolation, we establish the Brezis-Van Schaftingen-Yung formula and the Bourgain-Brezis-Mironescu formula in a more general setting of Ball Banach function space $X$. This generalization has a wide range of applications and, particularly, enables us to establish new fractional Sobolev and Gagliardo-Nirenberg inequalities in various function spaces, including Morrey spaces, mixed-norm Lebesgue spaces, variable Lebesgue spaces, weighted Lebesgue spaces, Orlicz spaces, and Orlicz-slice (generalized amalgam) spaces.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/2aD7VXda
54、夏学期第四周讲座三
报告题目：Clarkson-McLeod solutions of the fourth Painlev\'e equation: Asymptotics, applications, and problems
报告信息来源：复旦大学数学科学学院官网
报告人 Speaker：赵育求教授（中山大学）
时间 Datetime：2023-05-19 09:00-10:00
地点 Venue：腾讯会议ID:211-192-127
报告摘要 Abstract：
The Clarkson-McLeod solutions furnish a family of solutions to the fourth Painlev\'e equation that exponentially decay at positive infinity.Using the Deift-Zhou nonlinear steepest descent method, we derive the asymptotic behaviors for these solutions at the negative infinity.This completes a proof of the conjecture of Clarkson and McLeod on the asymptotics of this family of solutions. As applications, the Fredholm determinant,the total integrals of the Clarkson-McLeod solutions and the asymptotic approximations of the $\sigma$-form of this family of solutions are also derived. Furthermore, we find a determinantal representation of the $\sigma$-form of the Clarkson-McLeod solutions via an integrable operator with the parabolic cylinder kernel. This talk is based on joint work with Jun XIA and Shuai-Xia XU.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/gsWr7Zzq
53、夏学期第四周讲座二
报告题目：Robust Mallows-type model averaging approach
报告信息来源：浙江大学数学科学学院官网
报告人 Speaker：邹国华教授（首都师范大学）
时间 Datetime：2023-05-17 下午3点开始
地点 Venue：腾讯会议ID:451-180-251
报告摘要 Abstract：
Model averaging is an important tool for treating uncertainty from model selection process and fusing information from different models, and has been widely used in various fields. However, the most existing model averaging criteria are proposed based on the methods of ordinary least squares or maximum likelihood, which possess high sensitivity to outliers or violation of certain model assumption. For the mean regression, no optimal robust methods are developed. To fill this gap, in our paper, we propose an outlier-robust model averaging approach by Mallows-type criterion. The idea is that we first construct a generalized M (GM) estimator for each candidate model, and then build robust weighting schemes by the asymptotic expansion of the final prediction error based on the GM-type loss function. So we can still achieve a trustworthy result even if the dataset is contaminated by outliers in response and/or covariates. Asymptotic properties of the proposed robust model averaging estimators are established under some regularity conditions. The consistency of our weight estimators tending to the theoretically optimal weight vectors is also derived. We prove that our model averaging estimator is robust in terms of having bounded influence function. Further, we define the empirical prediction influence function to evaluate the quantitative robustness of the model averaging estimator. A simulation study and a real data analysis are conducted to demonstrate the finite sample performance of our estimators and compare them with other commonly used model selection and averaging methods.
报告人简介：邹国华，首都师范大学特聘教授。博士毕业于中国科学院系统科学研究所，是国家杰出青年基金获得者、“新世纪百千万人才工程”国家级人选、中国科学院“百人计划”入选者、享受国务院政府特殊津贴，曾获中国科学院优秀研究生指导教师称号。主要从事统计学的理论研究及其在经济金融、生物医学中的应用研究工作，在统计模型选择与平均、抽样调查的设计与分析、决策函数的优良性、疾病与基因的关联分析等方面的研究中取得了一系列重要成果，得到了国内外同行的好评与肯定，并被广泛引用。共出版教材2本，发表学术论文130余篇；主持和参加过近30项国家科学基金项目以及全国性的实际课题，提出的预测方法被实际部门所采用。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/SboOfc57
52、夏学期第四周讲座一
报告题目：规格约与格困难问题简介
报告信息来源：复旦大学数学科学学院官网
报告人 Speaker：温金明教授（暨南大学）
时间 Datetime：2023-05-17 09:30-10:30
地点 Venue：腾讯会议ID:120-600-488 密码：200433
报告摘要 Abstract：
在密码、通信、信号处理、全球定位系统等应用中，我们经常需要从一个带有噪声干扰的线性系统中重构一个整数参数信号。最大似然估计方法重构整数参数信号需要求解一个格困难问题，格规约是应用最广的格困难问题预处理方法。本报告首先介绍LLL等格规约算法在提升重构概率中的效果，然后介绍几个求解最短向量问题、逐次极小问题等格困难问题的高效算法，最后介绍格困难问题求解中的一些挑战和瓶颈。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/R6NSsoeD
51、夏学期第三周讲座三
报告题目：Nonlinear analysis and mathematical physcis seminar——Normalized discrete Ricci flow and community detection
报告信息来源：北京大学数学科学学院官网
报告人 Speaker：Yong Lin (Tsinghua University)
时间 Datetime：2023-05-11 16:00-17:00
地点 Venue：ZOOM会议 ID：890 7602 8232 密码: 020327
报告摘要 Abstract：
We prove the existence and uniqueness of solution of normalized discrete Ricci flow on graphs. We also use the discrete Ricci flow on the graph cut problems. These are the joint works with Bai, Lai, Lu, Wang and Yau.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/BzU5mzJZ
50、夏学期第三周讲座二
报告题目：样条有限元方法
报告信息来源：复旦大学数学科学学院官网
报告人 Speaker：李崇君（大连理工大学）
时间 Datetime：2023-05-10 10:00-11:00
地点 Venue：腾讯会议 ID：700-931-020, 密码: 200433
报告摘要 Abstract：
有限元是科学计算中用于求解偏微分方程的一类重要而且应用广泛的计算方法，其中一个核心问题是单元插值基函数（或形状函数）的构造。在报告中，我们将介绍如何利用多元样条方法构造平面四边形、多边形和三维空间若干单元的插值基函数，以获得具有高精度的样条有限元方法。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/MBOKxOMp
49、夏学期第三周讲座一
报告题目：Convergence of Randomized Kaczmarz Algorithms in Hilbert Spaces
报告信息来源：复旦大学数学科学学院官网
报告人 Speaker：郭昕（The University of Queensland）
时间 Datetime：2023-05-09 10:00-11:00
地点 Venue：腾讯会议 ID：432-637-714, 密码: 200433
报告摘要 Abstract：
The Kaczmarz algorithm was first introduced in 1937 to solve large systems of linear equations. Existing works on the convergence analysis of the randomized Kaczmarz algorithm typically provide exponential rates of convergence, with the base tending to one as the condition number of the system increases. Results of this kind do not work well for large systems of linear equations, and do not apply to the online algorithms on Hilbert spaces for machine learning. In this talk, we provide a condition number-free analysis, which leads to polynomial rates of weak convergence for the randomized Kaczmarz algorithm. We also show the applications to kernel-based machine learning.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/1jpGXo3J
48、夏学期第二周讲座二
报告题目:Stochastic Interpolations, Lipschitz Mass Transportation and Generative Learning
报告信息来源：复旦大学数学科学学院
报告人 Speaker：焦雨领副教授（武汉大学）
时间 Datetime：2023-05-07 15：00-16：00
地点 Venue：腾讯会议 ID：750-516-256 密码：200433
报告摘要 Abstract：
We construct a unit-time flow on the Euclidean space via stochastic interpolations, which unified recent ODE flows in generative learning. We study the well-posedness of the flow and establish the Lipschitz property of the flow map at time 1. We apply the Lipschitz mapping to several rich classes of probability measures on deriving functional inequalities with dimension-free constants, sampling and generative learning.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/Uu4MKDD6
47、夏学期第二周讲座一
报告题目：Quasi-interpolation for Data Mining
报告信息来源：复旦大学数学科学学院
报告人 Speaker：高文武教授（安徽大学）
时间 Datetime：2023-05-07 10：00-11：00
地点 Venue：腾讯会议 ID：750-516-256 密码：200433
报告摘要 Abstract：
Quasi-interpolation has been a useful tool for data mining. In this talk, I shall introduce some recent developments of quasi-interpolation of our work team, including constructing kernels with higher-order generalized Strang-Fix conditions, meshless symplectic schemes for numerical solutions of partial differential equations based on quasi-interpolation, study and construction quasi-interpolation under the probabilistic numerical framework such as quasi-interpolation for irregularly spaced data, optimality and regularization properties of quasi-interpolation, and so on.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/Qpobj02p
46、夏学期第一周讲座四
报告题目：Post-selection inference of high-dimensional logistic regression under case-control design
报告信息来源：浙江大学数据科学研究中心
报告人 Speaker：唐年胜教授（云南大学）
时间 Datetime：2023-04-27 下午14:00
地点 Venue：腾讯会议 ID：359-234-647
报告摘要 Abstract：
Confidence sets are of key importance in high-dimensional statistical inference. Under case-control study, a popular response-selective sampling design in medical study or econometrics, we consider the confidence intervals and statistical tests for single or low-dimensional parameters in high-dimensional logistic regression model. The asymptotic properties of the resulting estimators are established under mild regularity conditions. Furthermore, statistical tests for testing more general and complex hypotheses of the high-dimensional parameters are studied. The general testing procedures are proved to be asymptotically exact and has satisfactory power. Numerical studies including extensive simulations and a real data example confirm that the proposed method performs well in practical settings.
报告人简介：云南大学数学与统计学院教授，博士生导师，院长。“国家杰出青年科学基金”获得者，教育部“长江学者特聘教授”，教育部“新世纪优秀人才支持计划”入选者，国家百千万人才工程暨有突出贡献中青年专家，享受国务院政府特殊津贴。国际统计学会推选会员，国际数理统计学会会士（IMS Fellow）。云南省科技领军人才，云南省高等学校教学名师。现兼任教育部高等学校统计学类教学指导委员会委员、中国统计学会常务理事、中国现场统计研究会副理事长、中国现场统计研究会资源与环境统计分会副理事长、中国现场统计研究会高维数据统计分会副理事长；Statistics and Its Interface、Communications in Mathematics and Statistics等10余个杂志的编委或副主编。研究方向包括：生物统计、贝叶斯统计、统计诊断、缺失数据分析、高维数据分析、生存数据分析等，在JASA、Annals of Statistics、Biometrika、Journal of Econometrics、JMLR等学术期刊发表论文190余篇；出版学术专著5部、译著2部、教材1部。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/vsT3seoi
45、夏学期第一周讲座三
报告题目：Cracking the complexity of circuit-host interactions to design robust and predictable gene circuits
报告信息来源：复旦大学数学科学学院官网
报告人 Speaker：Xiaojun Tian（Arizona State University）
时间 Datetime：2023-04-28 10:00-11:00
地点 Venue：腾讯会议 ID：355716481，密码: 200438
报告摘要 Abstract：
Failure of modularity remains a significant challenge forassembling synthetic gene circuits with tested modules as they oftendo not function as expected.Hidden circuit-host interactions, such asgrowth feedback and resource competition,could significantlyimpair intended circuit function but are often overlooked. In thispresentation, I will discuss our latest research to use mathematicalmodeling to quantitatively understand and predict the impact ofnetwork topology, host physiology, and resource competition on thefunctional behaviors of gene circuits. First, we will discuss how theinterference of synthetic gene circuit function by growth feedbackdepends on circuit network topology and nutrient level. Second, wewill demonstrate how resource competition redirected desiredsuccessive cell fate transitions following a ‘winner-takes-all’rule.Third,we will highlight our control strategies against resourcecompetition, including a division of labor using microbial consortia,and negatively competitive regulation (NCR) controllers.Lastly, wewill discuss the effects of resource competition on circuit noisebehavior. Overall，our work will help us in the understanding andcontrol of circuit-host interactions toward engineeringrobustsynthetic gene circuits.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/H1aV8fPD
44、夏学期第一周讲座二
报告题目：Some discussions on MHD with strong boundary layers
报告信息来源：上海交通大学数学科学学院官网
报告人 Speaker：杨彤教授（香港理工大学）
时间 Datetime：2023-04-26 15:00-17:00
地点 Venue：腾讯会议 ID：235 179 851
报告摘要 Abstract：
In this talk, we will present some recent understanding on the MHD with strong boundary layers that includes well-posedness of boundary layer equations, instability mechanism and high Reynolds number limits in the fully nonlinear regime and the Prandtl-Hartmann regime. It aims to outline some unsolved problems in this direction to further understand the intrinsic mechanism of this classical system. The talk is based on some collaborations with Wei-xi Li, Chengjie Liu, Dehua Wang, Feng Xie and Zhu Zhang.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/dlHN0XoE
43、夏学期第一周讲座一
报告题目：Incompressible MHD Without Resistivity: structure and regularity
报告信息来源：上海交通大学数学科学学院官网
报告人 Speaker：Ronghua Pan（Georgia Institute of Technology）
时间 Datetime：2023-04-25 09:00-10:00
地点 Venue：腾讯会议 ID：132-634-986，密码: 230425
报告摘要 Abstract：
We study the global existence of classical solutions to the incompressible viscous MHD system without magnetic diffusion in 2D and 3D. The lack of resistivity or magnetic diffusion poses a major challenge to a global regularity theory even for small smooth initial data. However, the interesting nonlinear structure of the system not only leads to some significant challenges, but some interesting stabilization properties, that leads to the possibility of the theory of global existence of classical and/or strong solutions. This talk is based on joint works with Yi Zhou, Yi Zhu, Shijin Ding, Yingying Zeng, and Jingchi Huang.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/1Ga9BQ6f
42、春学期第八周讲座三
报告题目：On stability of incompressible flow driven by gravitation/buoyancy
报告信息来源：复旦大学数学科学学院官网
报告人 Speaker：孙永忠（南京大学）
时间 Datetime：2023-04-21 10:30-11:30
地点 Venue：腾讯会议ID:407-535-846
报告摘要 Abstract：
We consider the motion of viscous incompressible fluid under the action of gravitation/buoyancy modeled by the Boussinesq equations (in the absence of thermal conduction) in the $d$-dimensional domain $\mathbb{R}^{d-1}\times (0,1)$, $d=2,3$, which is an elliptic-parabolic-hyperbolic coupled nonlinear system. This system has a class of specific stationary solutions. Equipped the perturbed system (around the stationary solution) with suitable initial and boundary conditions we show global existence and decay rates of solutions with small initial data in Sobolev spaces. This in turn implies asymptotic stability of the corresponding stationary solution. Possible extensions to the inhomogeneous incompressible Navier-Stokes equations as well as some unsolved problems will also be discussed. These are joint work with Lihua Dong and Jianguo Li.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/LxEdnxN9
41、春学期第八周讲座二
报告题目：复域常微分方程的分类与超越亚纯解的可分解性
报告信息来源：复旦大学数学科学学院官网
报告人 Speaker：袁文俊（广州大学）
时间 Datetime：2023-04-19 14:30-15:30
地点 Venue：腾讯会议ID:964-829-232 密码：200433
报告摘要 Abstract：
本报告主要介绍复域中常微分方程的分类与超越亚纯解的可分解性. 首先介绍方程的解都具有 Painlev\'{e} 性质的分类以及由其引出特殊函数的基本概念和结果. Painlev\'{e} 超越函数就是其中重要的一类. 他们是由具有Painlev\'{e} 性质 ( 流动奇点都是极点 ) 的二阶常微分方程所定义的. 众所周知, 所有的线性常微分方程都具有Painlev\'{e} 性质, 但对于非线性方程结果大不相同. 一阶情形, L. Fuchs 给出了充分必要条件, 同时 P. Painlev\'{e} 和 L. Fuchs 还证明: 任何具有Painlev\'{e} 性质的一阶非线性常微分方程都可以经过适当的变换后化为 Weierstrass 方程或 Riccati 方程, 从而都是可用早已熟悉的函数包括特殊函数显式可积的. 换句话说, 就是不会产生新的函数. 其次介绍具有允许解的 Malmquist 型定理精细化分类以及具有可分解解的结果和未决问题.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/ppHj2jkt
40、春学期第八周讲座一
报告题目：On Second Maximal Subgroups of Even Order
报告信息来源：浙江大学数学科学学院官网
报告人 Speaker：缪龙（河海大学）
时间 Datetime：2023-04-18 16:00-17:00
地点 Venue：浙江大学紫金港校区海纳苑2幢210
报告摘要 Abstract：
Some different new classifications of even-order second maximal subgroups are induced by localizing the quantitative characteristics and embedding properties of some special subgroups. In the classification process, the relevant characterizations of different group classes are given considering their existence and combining the strengths and weaknesses of the second maximal subgroups.
报告人简介：
缪龙教授，2003年毕业于中国科技大学并获理学博士学位，2011年破格晋升为教授，现为河海大学教授、博士生导师。曾获霍英东教育基金会青年教师奖，江苏省数学成就奖，江苏省333工程培养对象，江苏省“青蓝工程”中青年学术带头人。曾赴德国Duisberg-Essen大学IEM研究所和西班牙University of Valencia访问研究方向是代数学，特别是有限群的结构理论和群类群系理论。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/CHJUXf3L
39、春学期第七周讲座三
报告题目：Quasineutral Euler limit for the Vlasov-Poisson-Landau system
报告信息来源：上海交通大学数学科学学院官网
报告人 Speaker：Renjun Duan（The Chinese University of Hong Kong）
时间 Datetime：2023-04-14 16:00-17:00
地点 Venue：腾讯会议 ID：528-939-603
报告摘要 Abstract：
The formal limit of the one-dimensional Vlasov-Poisson-Landau (VPL) system in the combined
small Knudsen and quasineutral regimes gives the compressible Euler system. In the talk I will
present a recent result on the construction of global-in-time small-amplitude smooth solutions
of the VPL system with an explicit rate of convergence to local Maxwellians whose fluid quantities are the Riemann rarefaction wave solutions to the limit Euler system. Joint with Dongcheng, Yang and Hongjun Yu.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/ziPA92f0
38、春学期第七周讲座二
报告题目：A Hamilton-Jacobi approach for nonlocal competition models of many species
报告信息来源：上海交通大学数学科学学院官网
报告人 Speaker：林经洋（俄亥俄州立大学）
时间 Datetime：2023-04-13 21:00-22:00
地点 Venue：腾讯会议 ID：804-813-494
报告摘要 Abstract：
The evolution of dispersal is a classical problem in evolutionary biology. The main question is to define the fittest dispersal rate for a population in a bounded domain. From the point of view of adaptive evolution, Perthame and Souganidis formulated a nonlocal competition model, in which the population is structured by space and a phenotypic trait variable, with the trait acting directly on the dispersal rate. For the small mutation limit, it was shown that the equilibrium population concentrates in the trait variable associated with the lowest dispersal rate, while remaining regular in the spatial variables. In this talk, we discuss the time-dependent solutions which exhibit moving Dirac concentrations in a fast timescale. We will derive, using the notion of Floquet bundles of parabolic equations, the constrained Hamilton-Jacobi equation describing the trajectory of the moving Dirac concentration.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/RRY173SB
37、春学期第七周讲座一
报告题目：Finite Element De Rham Complexes
报告信息来源：上海交通大学数学科学学院官网
报告人 Speaker： 黄学海 教授（上海财经大学）
时间 Datetime：2023-04-12 10:00-11:00
地点 Venue：腾讯会议 ID：125490222，密码: 745028
报告摘要 Abstract：
The construction of finite element De Rham complexes is presented in this talk. The polynomial De Rham complex and Koszul complex are combined to derive the decompositions of vectorial polynomial spaces. Traces of H(div) and H(curl) are shown. Different ways of constructing H(div)-conforming finite elements and H(curl)-conforming finite elements are discussed. Especially, with the help of the geometric decomposition and the tangential-normal decomposition, the basis functions of Lagrange element can be used to form the basis functions of H(div)-conforming finite elements and H(curl)-conforming finite elements, whose implementation is easy.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/gBj8ksGn
36、春学期第六周讲座二
报告题目：代数结构上的零和问题
报告信息来源：https://www.math.sjtu.edu.cn/Default/seminar/【上海交通大学数学科学学院】
报告人 Speaker：王国庆教授（天津矿业大学）
时间 Datetime：2023-04-07 14:00-15:00
地点 Venue：腾讯会议 ID：348-158-272 密码：112358
报告摘要 Abstract：
零和是组合数论的一个分支，其主要研究内容是群元素赋权下组合结构（包含集合、重集、图与超图等）中具有给定加法性质组合子结构的存在性、结构的刻画、以及相应的其他组合性质的探讨。零和研究起源于上世纪60年代Davenport常量的提出以及Erdős-Ginzburg-Ziv定理。本报告将介绍零和在群上的研究问题与发展，并结合报告人近期的一些研究工作，在半群和环等代数结构上对零和进行探讨。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/W0zzNVbU
35、春学期第六周讲座一
报告题目：Critical blow-up exponents in a chemotaxis system with indirect signal production
报告信息来源：https://www.math.pku.edu.cn/kxyj/xsbg/tlb/index.htm【北京大学数学科学学院】
报告人 Speaker：陶有山教授（上海交通大学）
时间 Datetime：2023-04-03 14:00-15:00
地点 Venue：腾讯会议 ID：107-930-142
报告摘要 Abstract：
Abstract:This talk addresses an initial-boundary problem for a quasilinear chemotaxis system with indirect attractant production, as arising in the modeling of effects due to phenotypical heterogeneity in microbial populations. Under the assumption that the rates $D$ and $S$ of diffusion and cross-diffusion are suitably regular functions of the population density, essentially exhibiting asymptotically algebraic behavior at large densities. A critical line in low-dimensional cases and two critical lines in higher-dimensional cases concerning the exponents of $D$ and $S$ for the occurrence of blow-up were found. This is a recent joint work with Prof. Michael Winkler (Paderborn).
报名链接：https://form.zju.edu.cn/#/dform/genericForm/q2XcgfTV
34、春学期第五周讲座二
报告题目：A Cone Story for Smooth Manifolds
报告信息来源：中国科学技术大学数学科学学院官网
报告人 Speaker：Li-Sheng Tseng（加利福尼亚大学尔湾分校）
时间 Datetime：2023-03-31 10:00-11:00
地点 Venue：腾讯会议 ID：659 493 495
报告摘要 Abstract：
For manifolds such as special holonomy and symplectic manifolds that are equipped with a geometrical structure specified by a distinguished closed form, we will motivate the usefulness of considering pairs of differential forms that are linked together by a map of the distinguished form. We will show how this lead to new notions of Morse theory and flat connections, and also novel Yang-Mills type functionals. This talk is based on joint works with David Clausen, Xiang Tang, and Jiawei Zhou.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/ymTLWSUC
33、春学期第五周讲座一
报告题目：Distributed Adaptive Filtering and Estimation in Network Systems
报告信息来源：华东师范大学数学科学学院官网
报告人 Speaker：谢思宇 教授(电子科技大学)
时间 Datetime：2023-03-29 10:00-11:00
地点 Venue：腾讯会议 ID：866 843 414
报告摘要 Abstract：
With the development of network technology, distributed adaptive filtering (or estimation) algorithms have been widely used in many practical situations. Although the distributed filtering algorithms can be applied to a wide class of signals and requires no assumptions on the statistics of regression vectors and measurements, when it comes to stability and performance evaluation, some independency or stationarity conditions are necessarily required to carry out the theoretical analysis. In this talk, we will show that both the stability and the tracking performance bounds of a class of distributed adaptive filtering and estimation algorithms can be established under a general cooperative information condition, which needs neither independence nor stationarity of the system signal. We will further show that our information condition is actually a necessary one for a wide class of stochastic signals with decaying dependence. Furthermore, the weakest possible information condition also implies that the distributed adaptive filter can work well even if any individual filter is not stable due to lack of necessary information (i.e., the covariance matrix for each individual regressor is degenerate), which is a natural property for distributed algorithms but has not been justified rigorously in the existing literature.
报告人简介：
谢思宇，女，电子科技大学教授，博导，国家级青年人才计划入选者。1991年出生于四川省遂宁市，2013年获得北京航空航天大学理学学士学位，2018年获得中国科学院数学与系统科学研究院理学博士学位，导师为郭雷院士，2019-2022年在美国韦恩州立大学从事博士后研究工作，合作导师为王乐一教授。近年来以多个体网络系统为研究对象，瞄准分布式滤波、估计、优化及其在电力系统中的应用等关键科学问题展开研究，发表SCI期刊论文20余篇，包括控制方向的顶级期刊IEEE TAC、Automatica、SIAMCON，和电力系统方向的顶级期刊IEEE TSG、IEEE TITS、IJEPES等。曾获得中国科学院大学优秀博士学位论文、 IEEE CSS Beijing Chapter 青年作者奖、博士生国家奖学金等荣誉和称号。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/q6PBmAkP
32、春学期第四周讲座二
报告题目：Theory of Functional PCA for noisy and discretely observed data
报告信息来源：http://www.math.zju.edu.cn/【浙江大学数学科学学院官网】
报告人 Speaker：姚方教授（北京大学）
时间 Datetime：2023-03-24 15:00开始
地点 Venue：腾讯会议 ID：545-515-268
报告摘要 Abstract：
Functional data analysis is an important research field in statistics which treats data as random functions drawn from some infinite-dimensional functional space, and functional principal component analysis (FPCA) plays a central role for data reduction and representation. After nearly three decades of research, there remains a key problem unsolved, namely, the perturbation analysis of covariance operator for diverging number of eigencomponents obtained from noisy and discretely observed data. This is fundamental for studying models and methods based on FPCA, while there has not been much progress since the result obtained by Hall et al. (2006) for a fixed number of eigenfunction estimates. In this work, we establish a unified theory for this problem, deriving the moment bounds of eigenfunctions and asymptotic distributions of eigenvalues for a wide range of sampling schemes. We also exploit double truncation to derive the uniform convergenceof such estimated eigenfunctions. The technical arguments in this work are useful for handling the perturbation series of discretely observed functional data and can be applied in models and methods involving inverse using FPCA as regularization, such as functional linear regression.
报告人简介：
姚方，国家高层次人才，北京大学讲席教授，北大统计科学中心主任、概率统计系主任，数理统计学会与美国统计学会会士。2000年本科毕业于中国科学技术大学，2003获得加利福尼亚大学戴维斯分校统计学博士学位，曾任职于多伦多大学统计科学系长聘正教授。至今担任9个国际统计学核心期刊主编或编委，包括《加拿大统计学期刊》主编、顶级期刊《北美统计学会会刊》和 《统计年刊》的编委。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/18nTWxUe
31、春学期第四周讲座一
报告题目：Stability threshold of the Couette flow at high Reynolds number
报告信息来源：https://www.math.sjtu.edu.cn【上海交通大学数学科学学院官网】
报告人 Speaker：章志飞（北京大学）
时间 Datetime：2023-03-22 15:00-17:00
地点 Venue：腾讯会议 ID：738-365-909
报告摘要 Abstract：
Since Reynolds’experiment in 1883, hydrodynamic stability has been an active field. This field focuses on how laminar flow becomes unstable and transit to turbulence. In order to understand the transition mechanism, Trefethen et al proposed the transition threshold problem. In this lecture, I will introduce some key ingredients of the proof for the stability threshold of the 2-D Couette flow and 3-D Couette flow.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/iVEtIknj
30、春学期第三周讲座二
报告题目：Eyes and Brain: Cancer Diagnosis Applications on CT Images with AI
报告信息来源：https://www.math.sjtu.edu.cn【上海交通大学数学科学学院官网】
报告人 Speaker：Jingchen Ma（Columbia University Medical Center）
时间 Datetime：2023-03-16 10:30-11:30
地点 Venue：腾讯会议 ID：784-585-475 密码：489792
报告摘要 Abstract：
Cancer is one of top killer worldwide. Elimiating cancer is our ultimate goal. Seeing the cancer on medical image is the very first step of our goal.In this talk, I will briefly introduct several medical image applications about cancer detection/segmentation/diagnosis on CT images with machine learing/deep learning/neural artitecture search. The audiences will get some idea about what AI see and sense of cancer images.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/TMP7gP2z
29、春学期第三周讲座一
报告题目：Some recent results on Turing instability of the periodic solutions for the diffusive system
报告信息来源：https://www.math.sjtu.edu.cn【上海交通大学数学科学学院官网】
报告人 Speaker：衣凤岐（大连理工大学）
时间 Datetime：2023-03-15 08:00-09:45
地点 Venue：腾讯会议 ID：701-362-510
报告摘要 Abstract：
In this talk, I will report our recent results on Turing instability of the periodic solutions for the diffusive systems: the system of reaction-diffusion equations (with/without time delay), the patch models and the system of reaction-diffusion equations with coupled layers. Sufficient conditions are derived to determined Turing instability of the periodic solutions for these systems.
报名链接： https://form.zju.edu.cn/#/dform/genericForm/IAyBGIoU
28、春学期第二周讲座二
报告题目：Greedy Algorithm and Projection Pursuit Regression
报告信息来源：http://www.math.zju.edu.cn/【浙江大学数学科学学院】
报告人 Speaker：夏应存（新加坡国立大学）
时间 Datetime：2023-03-10 10:00开始
地点 Venue：腾讯会议 ID：309-883-903
报告摘要 Abstract：
Projection Pursuit Regression (PPR) has played an important role in the development of statistics and machine learning. However, as a statistical learning method, PPR has not yet demonstrated an accuracy comparable to other methods such as Random Forests (RF) and Artificial Neural Networks (ANN). In this paper, we revisit the estimation of PPR and propose a greedy algorithm and an ensemble approach via feature bagging,hereafter referred to as ePPR. Compared to Random Forest (RF), ePPR has two main advantages: (1) its theoretical consistency can be proved for more general regression functions, as long as they are continuous, and higherconsistency rates can be obtained; and (2) ePPR does notsplit the samples, so each term of the PPR is estimatedusing the whole data, which makes the estimation moreefficient and guarantees the smoothness of the estimator.ePPR is also easier to tune and train than ANN. Extensivecomparisons on real data sets show that ePPR is noticeablymore efficient in regression and classification than RF andother competitors.
报告人简介：
夏应存，新加坡国立大学统计与数据科学系教授。研究兴趣包括非参数回归，高维数据分析，疾病传播统计建模等。研究成果发表在AOS,ASAJRSSB,Biometrika, JOE,PNAS等期刊. Nature News等多个学术媒体对其提出的疾病跨域传播模型做了专题报道。JRSSB, Statistical ScienceFaStatistica Sinica対其论文迸行了公开讨论。夏应存曾在暨南大学工作多年，获国务院侨办颁发的“优秀教师”称号。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/lhGftXuj
27、春学期第二周讲座一
报告题目：Bulk universality and quantum unique ergodicity of random band matrices
报告信息来源：https://math.fudan.edu.cn/【复旦大学数学科学学院】
报告人 Speaker：杨帆（清华大学）
时间 Datetime：2023-03-09 13:30-14:30
地点 Venue：腾讯会议 ID：665-541-454
报告摘要 Abstract：
Consider a general class of random band matrices $H$ on the $d$-dimensional lattice of linear size $L$. The entries of $H$ are independent centered complex Gaussian random variables with variances $s_{xy}$, which have a banded profile so that $s_{xy}$ is negligible if $|x-y|$ exceeds the band width $W$. In dimensions $d\ge 7$, assuming that $W\geq L^\delta $ for a small constant $\delta>0$, we prove the deloclaization and quantum unique ergodicity (QUE) of the bulk eigenvectors of $H$. Furthermore, we prove the bulk universality of $H$ under the condition $W \gg L^{95/(d+95)}$. In the talk, I will discuss a new idea for the proof of the bulk universality through QUE, which verifies the conjectured connection between QUE and bulk universality. The proof of QUE is based on a local law for the Green's function of $H$ and a high-order $T$-expansion developed recently. Based on Joint work with Changji Xu, Horng-Tzer Yau and Jun Yin.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/P8gLqfu1
26、春学期第一周讲座二
报告题目：On Bernstein Theorem of Affine Maximal Equation
报告信息来源：https://www.math.sjtu.edu.cn/【上海交通大学数学科学学院】
报告人 Speaker：杜式忠（汕头大学）
时间 Datetime : 2023-03-02 15:00-16:00
地点 Venue : 腾讯会议 ID: 116 222 407
报告摘要 Abstract :
Bernstein problem for affine maximal type hypersurfaces has been a core problem in affine geometry. A conjecture proposed firstly by Chern (Proc. Japan-United States Sem., Tokyo, 1977, 17-30) for entire graph and then reformulated by Calabi (Amer. J. Math., 104, 1982, 91-126) to its fully generality asserts that any Euclidean complete, affine maximal type, locally uniformly convex C^4-hypersurface in R^{N+1} must be an elliptic paraboloid. The problem remained open until a milestone made by Trudinger-Wang in [40] (Invent. Math., 140, 2000, 399-422), where the Chern's conjecture was solved completely for dimension N=2 and \theta=3/4. At the same time, it was conjectured by Trudinger-Wang (see also two survey papers by Trudinger [38,39] for the details) that the Bernstein property of the affine maximal hypersurfaces should hold on lower dimensional spaces and fail to hold for higher dimensional cases. On the past twenty years, much efforts were done toward higher dimensional issues but not really successful yet, even for the case of dimension N=3. In this talk, we will present some known results and new results for the problem.
报告人简介：
杜式忠，汕头大学副教授。主要从事完全非线性偏微分方程与几何分析相关的理论研究，主持国家自然科学基金面上项目一项、青年基金一项。文章发表于Transactions of AMS，Calc. Var. & PDEs., Journal of Differential Equations等数学刊物上。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/ZLvS6SJ4
25、春学期第一周讲座一
报告题目：Dynamics of Composite Symplectic Dehn Twists
报告信息来源：https://www.math.utsc.edu.cn/【中国科学技术大学数学科学学院学术报告】
报告人 Speaker：薛金鑫（清华大学）
时间 Datetime : 2023-03-02 10:00-11:00
地点 Venue : 腾讯会议 ID: 879 699 629
报告摘要 Abstract :
It is classically known in Nielson-Thurston theory that the mapping class group of a hyperbolic surface is generated by Dehn twists and most elements are pseudo Anosov. Pseudo Anosov elements are interesting dynamical objects. They are featured by positive topological entropy and two invariant singular foliations expanded or contracted by the dynamics. We explore a generalization of these ideas to symplectic mapping class groups. With the symplectic Dehn twists along Lagrangian spheres introduced by Arnold and Seidel, we show in various settings that the compositions of such twists has features of pseudo Anosov elements, such as positive topological entropy, invariant stable and unstable laminitions, exponential growth of Floer homology group, etc. This is a joint work with Wenmin Gong and Zhijing Wang.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/6dRLQx8z
24、冬学期第七周讲座二
报告题目：数学物理反问题与逆向思维
报告信息来源：https://www.math.sjtu.edu.cn/【上海交通大学数学科学学院学术报告】
报告人 Speaker：程晋（复旦大学数学科学院&上海市现代应用数学重点研究室）
时间 Datetime : 2022-12-23 16:00-17:00
地点 Venue : 腾讯会议 ID: 885-184-069 密码：221223
报告摘要 Abstract :
数学物理反问题的研究是现代应用数学研究的一个热点研究方向，具有重要的实际背景和理论研究价值，研究成果有很强的应用前景。对于反问题的研究学者来讲，如何提出有意义的反问题是一个令人困惑的难题。在本报告中，我们通过逆向思维的方式给出若干例子，说明如何合理地提出具有研究价值的反问题，并指出如何将现代应用数学的成果融入反问题的研究当中，解决一些工程和实际问题的关键的难点问题。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/neJweRfT
23、冬学期第七周讲座一
报告题目：On spectral and inverse spectral problems related to non-smooth solitons of Novikov equation
报告信息来源：https://www.math.sjtu.edu.cn/【上海交通大学数学科学学院学术报告】
报告人 Speaker：常向科（中国科学院数学与系统科学研究院）
时间 Datetime : 2022-12-22 14:00-15:00
地点 Venue : 腾讯会议 ID: 619-755-887
报告摘要 Abstract :
As non-smooth solitons, peakons are special weak solutions of a class of nonlinear partial differential equations modelling non-linear phenomena such as the breakdown of regularity and the onset of shocks. One natural concept of peakons is dictated by the distributional compatibility of the Lax pairs. Due to the Lax integrability, the inverse spectral method is a powerful tool for the study of these solutions. In this talk, I will introduce some known results for the Camassa-Holm equation as well as our recent progress on Novikov equation.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/uAI8svzt
22、冬学期第六周讲座二
报告题目：Singular Stochastic Differential Equations
报告信息来源：https://www.math.sjtu.edu.cn/【上海交通大学数学科学学院学术报告】
报告人 Speaker：张希承（北京理工大学）
时间 Datetime : 2022-12-16 15:00-16:00
地点 Venue : 腾讯会议 ID: 314-533-233 密码：123456
报告摘要 Abstract :
The development of stochastic differential equations has a long history. In recent years, the study of singular SDEs is attracted much attention not only in mathematics, but also in applications. In this talk I will survey some recent results about singular stochastic differential equations including the McKean-Vlasov SDEs.
报告人简介：
张希承，北京理工大学数学与统计学院教授。2013年获国家自然科学基金杰出青年项目资助，2016年获教育部高层次人次支持计划，迄今已发表学术论文一百余篇。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/omzBIyL4
21、冬学期第六周讲座一
报告题目：ORBITAL STABILITY OF SOLITONS FOR A CLASS OF QUASILINEAR SHALLOW WATER EQUATIONS
报告信息来源：https://www.math.sjtu.edu.cn/【上海交通大学数学科学学院学术报告】
报告人 Speaker：李骥（华中科技大学）
时间 Datetime : 2022-12-15 14:00-15:00
地点 Venue : 腾讯会议 ID: 699-541-607
报告摘要 Abstract :
We first review some aspects of soliton for the KdV equation. Then we introduce a class of quasilinear shallow water equations: Camassa-Holm(CH), Degasperis-Procesi (DP), and the modified Camassa-Holm. We explain how their solitons could be proved stable by Lyapunov functional methods or by Variational method. We also explain how the Lyapunov functional method could be localized to prove multi-soliton stability for the DP case.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/cyB1nNiS
20、冬学期第五周讲座二
报告题目：Residual Permutation Test for High-Dimensional Regression Coefficient Testing
报告信息来源：https://www.stat-center.pku.edu.cn/【北京大学统计科学中心】
报告人 Speaker：Yuhao Wang (Tsinghua University)
时间 Datetime : 2022-12-08 14:00-15:00
地点 Venue : 腾讯会议 ID: 836-392-792
报告摘要 Abstract :
We consider the problem of testing whether a single coefficient is equal to zero in high-dimensional fixed-design linear models. In the high-dimensional setting where the dimension of covariates $p$ is allowed to be in the same order of magnitude as sample size $n$, to achieve finite-population validity, existing methods usually require strong distributional assumptions on the noise vector (such as Gaussian or rotationally invariant), which limits their applications in practice. In this paper, we propose a new method, called \emph{residual permutation test} (RPT), which is constructed by projecting the regression residuals onto the space orthogonal to the union of the column spaces of the original and permuted design matrices. RPT can be proved to achieve finite-population size validity under fixed design with just exchangeable noises, whenever $p < n / 2$. Moreover, RPT is shown to be asymptotically powerful for heavy tailed noises with bounded $(1+t)$-th order moment when the true coefficient is at least of order $n^{-t/(1+t)}$ for $t \in [0,1]$. We further proved that this signal size requirement is essentially optimal in the minimax sense. Numerical studies confirm that RPT performs well in a wide range of simulation settings with normal and heavy-tailed noise distributions.
报告人简介：
Yuhao Wang is an assistant professor in the Institute of Interdisciplinary Information Sciences (IIIS), Tsinghua University. Before that, Yuhao was a postdoctoral research associate at the Statistical Laboratory, which is part of the Department of Pure Mathematics and Mathematical Statistics at the University of Cambridge and a Ph.D. student from the Department of Electrical Engineering and Computer Science at Massachusetts Institute of Technology. Yuhao's main research focus is causal inference, experimental design, high dimensional statistics and distribution-free hypothesis tests.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/LwEYYejn
19、冬学期第五周讲座一
报告题目：Convergence analysis of the Multi-scale Deep Neural Network (MscaleDNN)
报告信息来源：https://www.math.sjtu.edu.cn/【上海交通大学数学科学学院学术报告】
报告人 Speaker：汪波（湖南师范大学）
时间 Datetime : 2022-12-07上午 9:30 -11:30
地点 Venue : 腾讯会议 ID:917277083 密码:605320
报告摘要 Abstract :
In this talk, we will present a numerical analysis for the convergence of the machine learning algorithm with Multi-scale neural network. We prove that the training process for some one layer neural networks with gradient descent optimization algorithm tends to diffusion process in the Fourier spectral domain as the learning rate goes to zero. Consequently, the multi-scale neural network is shown to have diffusion coefficients covering a wider range of frequency compared to fully connected neural network.
报告人简介：
汪波，湖南师范大学数学与统计学院教授，国家高层次青年人才计划入选者。2011年在湖南师范大学获计算数学博士学位。2011年至2013年在新加坡国立大学从事博士后研究工作。主要研究方向包括超材料中电磁场计算的DG方法、波散射问题高精度方法、界面问题HDG方法、多层媒质中的快速多极法等。在《SIAM J. Sci. Comp.》、《SIAM J. Numer. Anal.》、《Comput. Methods Appl. Mech. Engrg.》、《SIAM J. Appl. Math.》等国内外著名刊物发表论文20多篇，主持国家基金4项。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/zzhHTkF4
18、冬学期第四周讲座二
报告题目：A statistical approach to feature-based dynamic pricing
报告信息来源：https://www.stat-center.pku.edu.cn/【北京大学统计科学中心】
报告人 Speaker：Yongyi Guo（哈佛大学）
时间 Datetime : 2022-12-01 上午 9:00 -10:00
地点 Venue : 腾讯会议 ID: 402-713-114
报告摘要 Abstract :
Dynamic pricing is one of the most common examples of online decision problems with continuous action space. With the development of e-commerce and the massive real-time data in online platforms today, feature-based (or contextual) pricing models have become increasingly important. In this work, we study the feature-based dynamic pricing problem where the market value of a product is linear in its observed features plus unobservable market noise whose distribution is unknown. To reduce modeling bias, we assume that the market noise density falls into a non-parametric class. We propose a dynamic statistical learning and decision making policy that minimizes regret by combining online decision making and semi-parametric statistical estimation from a generalized linear model with an unknown link. Specifically, we provide non-asymptotic uniform error bounds for kernel type regression estimators, which enable us to control the regret while learning the model efficiently. Under mild conditions, our proposed algorithm achieves near optimal regret at the same order as the lower bound when the market noise distribution is parametric (\Omega(\sqrt{T})). The performance of the algorithm is also demonstrated through intensive simulations and real data experiments.
报告人简介：
Yongyi Guo is a postdoctoral research fellow in the Department of Statistics, Harvard University, hosted by Professor Susan A. Murphy. In the fall of 2023, she will start as an assistant professor at the Department of Statistics, University of Wisconsin-Madison. Yongyi obtained her Ph.D. degree from the Department of Operations Research and Financial Engineering at Princeton University, advised by Professor Jianqing Fan. Before that, she obtained her Bachelor’s degree from the School of Mathematical Sciences, Peking University. Her research interests lie in statistics, machine learning and data-driven decision-making.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/MeP8Mdc8
17、冬学期第四周讲座一
报告题目：Functional data analysis with covariate-dependent mean and covariance structures
报告信息来源：https://www.math.zju.edu.cn
报告人 Speaker：林华珍教授（西南财经大学)
时间 Datetime : 2022-11-28 下午 16:00 开始
地点 Venue : 腾讯会议 ID: 441-837-276
报告摘要 Abstract :
Functional data analysis has emerged as a powerful tool in response to the ever increasing resources and efforts devoted to collecting information about response curves or anything varying over a continuum. However,limited progress has been made to link the covariance structure of response curves to external covariates, as most functional models assume a common covariance structure. We propose a new functional regression model with covariate-dependent mean and covariance structures. Particularly，by allowing the variances of the random scores to be covariate-dependent, we identify eigenfunctions for each individual from the set of eigenfunctions which govern the patterns of variation across all individuals, resulting in high interpretability and prediction power. We further propose a new penalized quasi-likelihood procedure,which combines regularization and B-spline smoothing, for model selection and estimation, and establishthe
convergence rate and asymptotic normality for the proposed estimators. The utility of the method is demonstrated via simulations as well as an analysis of the Avon Longitudinal Study of Parents and Children on parental effects on the growth curves of their offspring, which yields biologically interesting results.
报告人简介:林华珍,西南财经大学教授,统计研究中心主任,国际数理统计学会IMS-fellow,国家杰出青年科学基金获得者，享受国务院政府特殊津贴专家。主要研究方向包括非参数方法、转换模型、生存数据分析、函数型数据分析、潜变量分析、时空数据分析。研究成果发表在包括国际统计学四大顶级期刊AoS、JASA、JRSSB、Biometrika和计量经济学顶级期刊JOE及JBES 上。多次主持国家基金项目，包括国家杰出青年基金及自科重点项目。林华珍教授是国际IMS-China、IBS-CHINA 及 ICSA-China委员，中国现场统计研究会数据科学与人工智能分会理事长,第九届全国工业统计学教学研究会副会长，中国现场统计研究会多个分会的副理事长。先后是国际统计学权威期刊《Biometrics》、《Scandinavian Journal of Statistics》、《Journal of Business & Economic Statistics》、《Canadian Journal of Statistics》、《Statistics and Its Interface》《Statistical Theory and Related Fields》的Associate Editor，国内权威或核心学术期刊《数学学报》(英文)、《应用概率统计》、《系统科学与数学》、《数理统计与管理》编委。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/H7h85zUm
16、冬学期第三周讲座二
报告题目：A new sharp-interface model for simulating solid-state dewetting problems
报告信息来源：https://www.math.sjtu.edu.cn/【上海交通大学数学科学学院学术报告】
报告人 Speaker：蒋维 (武汉大学)
时间 Datetime : 2022-11-24 下午 16:00-17:00
地点 Venue : 腾讯会议 ID: 159320797 密码: 625401
报告摘要 Abstract :
Solid-state dewetting is a ubiquitous phenomenon in materials science, and it describes the agglomeration of solid thin films into arrays of isolated particles on a substrate. In recent years, solid-state dewetting has found wide applications in modern technology, and much efforts have been devoted to understanding this important phenomenon. One of the effective tools for modeling and simulations of solid-state dewetting was the sharp-interface model proposed by my group [see Phys. Rev. B, 91:045303, 2015; SIAM J. Appl. Math., 80:1654, 2020]. However, these sharp-interface models belong to free boundary problems, which explicitly include surface diffusion and contact line migration. It is very difficult to design efficient numerical algorithms for solving the sharp-interface models. On the other hand, lots of pinch-off events will occur when a long island film evolves by solid-state dewetting, but the previous sharp-interface models can not automatically handle with topological events. In order to tackle these difficulties, we propose a new sharp-interface model with the thickness-dependent surface energy for simulating solid-state dewetting by removing the singularity of the triple point among the film, vapor and substrate phases. The new model is only needed to solve in a fixed domain, and it can automatically capture “topological events”. Numerical results demonstrate the high performance of the new model.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/GNtqdrD4
15、冬学期第三周讲座一
报告题目：Well-posedness of classical solutions to the vacuum free boundary problem of the viscous Saint-Venant system for shallow waters
报告信息来源：https://www.math.sjtu.edu.cn/【上海交通大学数学科学学院学术报告】
报告人 Speaker：王跃循 (兰州大学)
时间 Datetime : 2022-11-22 上午 10:00-11:00
地点 Venue : 腾讯会议 ID: 722893254 密码: 221122
报告摘要 Abstract :
We establish the local-in-time well-posedness of classical solutions to the vacuum free boundary problem of the viscous Saint-Venant system for shallow waters derived rigorously from incompressible Navier-Stokes system with a moving free surface by Gerbeau and Perthame. Our solutions are smooth to the moving boundary, although the initial height degenerates as a singularity of the distance function to the vacuum boundary.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/cyYW2YUE
14、冬学期第二周讲座二
报告题目：Modulated Free Energy and Mean Field Limit
报告信息来源：https://www.math.sjtu.edu.cn/【上海交通大学数学科学学院学术报告】
报告人 Speaker：王振富(北京大学)
时间 Datetime : 2022-11-18 下午 15:00-16:00
地点 Venue : 腾讯会议 ID: 758-786-714 密码：221118
报告摘要 Abstract :
We proves the mean field limit and quantitative estimates for many-particle systems with singular attractive interactions between particles. As an important example, a full rigorous derivation (with quantitative estimates) of the Patlak-Keller-Segel model in optimal subcritical regimes is obtained for the first time. To give an answer to this longstanding problem, we take advantage of a new modulated free energy and we prove some precise large deviation estimates encoding the competition between diffusion and attraction. This modulated free energy approach can also treat the systems with a wide range of repulsive kernels, including the vanishing viscosity case. Based on joint works with D. Bresch and P.-E. Jabin.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/1cwNVha7
13、冬学期第二周讲座一
报告题目：Parameter estimation for mixed fractional stochastic volatility model
报告信息来源：https://www.math.pku.edu.cn/【北京大学数学科学学院学术报告】
报告人 Speaker：Weilin Xiao(Zhejiang University)
时间 Datetime : 2022-11-17 下午 15:10-17:00
地点 Venue : 腾讯会议 ID: 935-3935-7603 密码：123456
报告摘要 Abstract :
During the last two decade, the memory phenomenon have received increasing popularity for modelling market behaviour for both the return and the volatility of financial assets. Based on discrete-sampled observations, this paper considers the statistic inference of all the unknown parameters in a special stochastic processes with the memory phenomenon, namely, mixed fractional stochastic volatility model. The usual asymptotic properties, including strong consistency and asymptotic normality, are established under the long-span asymptotics, when the sampling interval is fixed and the sample size increases as the time span increases. The extension, when the volatility process has measurement errors, is also discussed. Monte Carlo experiments are performed to demonstrate the feasibility and effectiveness of the proposed method.
报告人介绍：
肖炜麟，华南理工大学工商管理学院博士，浙江大学管理学院副教授、博士生导师，浙江大学资本市场研究中心副主任。主要研究领域为金融风险管理、金融计量、碳金融和机器学习等，在《Journal of Econometrics》、《Journal of Business and Economics Statistics》、《Econometric Theory》、《Science China: Mathematics》、《中国科学: 数学》、《管理科学学报》、《系统工程理论与实践》等期刊上发表多篇学术论文。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/ISefDmog
12、冬学期第一周讲座二
报告题目：A unified generalization of inverse regression via adaptive column selection
报告信息来源：http://math.xjtu.edu.cn/【西安交通大学数学与统计学院学术报告】
报告人 Speaker：骆威（浙江大学）
时间 Datetime : 2022-11-11 上午 10:00-11:30
地点 Venue : 腾讯会议 ID: 927-217-234
报告摘要 Abstract :
Higher-order inverse regression methods are commonly known as more powerful sufficient dimension reduction (SDR) methods than the popularly used sliced inverse regression (SIR) in the population level. However, due to the convention of essentially conducting singular value decomposition on the ambient candidate matrices, these methods suffer from the excessive number of parameters in the sample level and have not been systematically generalized under the high-dimensional settings like SIR. In this paper, we break the convention of using the ambient candidate matrices in these methods, and instead apply a novel column-selection strategy on their candidate matrices that substantially lowers down the working number of parameters to being comparable with SIR. Then, for the first time of the literature, we generalize the higher-order inverse regression methods, as well as their ensembles, towards sparsity under the high-dimensional settings in a uniform manner. The dimension of the predictor is allowed to diverge with the sample size in nearly an exponential order, and no additional restrictions are imposed on the data other than those commonly seen in the high-dimensional literature. For completeness of theory, we also study the column-selection strategy towards the estimation efficiency under the conventional low-dimensional settings. These results are illustrated by simulation studies and a real data application at the end.
报告人介绍：
骆威，浙江大学研究员，博士生导师，于2014年毕业于美国宾夕法尼亚州立大学，之后任职于美国Baruch College,于2018年加入浙江大学。骆威博士的研究方向包括充分降维和因果推断，在Annals of Statistics, Biometrika, JRSSB等统计国际学术期刊上发表了多篇论文。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/ETC89PB8
11、冬学期第一周讲座一
报告题目：Large Deviation Principle for Empirical Measures of Once-reinforced Random Walks on Finite Graphs
报告信息来源：https://math.sjtu.edu.cn/Default/seminar/【上海交通大学数学科学学院学术报告】
报告人 Speaker：刘勇 教授（北京大学）
时间 Datetime : 2022-11-09 下午 14:00-15:00
地点 Venue : 腾讯会议 ID: 577-755-864 密码：123456
报告摘要 Abstract :
The once-reinforced random walk (ORRW) is a kind of non-Markov process with the transition probability only depending on the current weights of all edges. The weights are set to be 1 initially. At the first time an edge is traversed, its weight is changed to a positive parameter δ at once, and it will remain in δ. We introduce a log-transforms of exponential moments of restricted empirical measure functionals, and prove a variational formula for the limit of the functionals through a variational representation given by a novel dynamic programming equation associated with these functionals. As a corollary, we deduce the large deviation principle for the empirical measure of the ORRW. Its rate function is decreasing in δ, and is not differentiable at δ=1. Moreover, we characterize the critical exponent for the exponential integrability of a class of stopping times including the cover time and the hitting time. For the critical exponent, we show that it is continuous and strictly decreasing in δ, and describe a relationship between its limit (as δ→0) and the structure of the graph. This is a joint work with Dr. Xiangyu Huang and Professor Kainan Xiang.
报告人介绍：
刘勇教授，1999年在北京大学数学学院获得博士学位，在中国科学与数学与系统科学研究院作博士后，目前是北京大学数学学院教授。主要研究兴趣是大偏差理论，随机分析和随机偏微分方程。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/yRMe0Pvm
10、秋学期第八周讲座二
报告题目：Stochastic Navier-Stokes equations via convex integration
报告信息来源：https://math.sjtu.edu.cn/Default/seminar/【上海交通大学数学科学学院学术报告】
报告人 Speaker：朱湘禅（中科院数学与系统科学研究院应用所）
时间 Datetime : 2022-11-04 下午 14:00-15:00
地点 Venue : 腾讯会议 ID: 801-128-324 密码：123456
报告摘要 Abstract :
In this talk I will talk about our recent work on the three dimensional stochastic Navier-Stokes equations via convex integration method. First we establish non-uniqueness in law,existence and non-uniqueness of probabilistically strong solutions and non-uniqueness of the associated Markov processes.Second we prove existence of infinitely many stationary solutions as well as ergodic stationary solutions to the stochastic Navier-Stokes and Euler equations. Moreover, we are able to make conclusions regarding the vanishing viscosity limit and the anomalous dissipation. Finally I will show global-in-time existence and non-uniqueness of probabilistically strong solutions to the three dimensional Navier--Stokes system driven by space-time white noise. In this setting, the convective term is ill-defined in the classical sense and probabilistic renormalization is required.
报告人介绍：
朱湘禅，中科院数学与系统科学研究院应用所研究员，2012年于北京大学和德国比勒菲尔德大学获得博士学位。主要研究方向是随机分析和随机偏微分方程，具体包括奇异随机偏微分方程和随机流体方程等。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/6EKKbkkP
9、秋学期第八周讲座一
报告题目：Divide-and-Conquer: A Distributed Hierarchical Factor Approach to Modeling Large-Scale Time Series Data
报告信息来源：西南财经大学数据科学与商业智能联合实验室
报告人 Speaker：高照省（浙江大学数据科学研究中心）
时间 Datetime : 2022-11-01 上午 10:00-11:00
地点 Venue : 腾讯会议 ID: 907-669-962
报告摘要 Abstract :
In this talk, I will introduce a hierarchical approximate-factor approach to analyzing high-dimensional, large-scale heterogeneous time series data using distributed computing. The new method employs a multiple-fold dimension reduction procedure using Principal Component Analysis (PCA) and shows great promises for modeling large-scale data that cannot be stored nor analyzed by a single machine. Each computer at the basic level performs a PCA to extract common factors among the time series assigned to it and transfers those factors to one and only one node of the second level. Each second-level computer collects the common factors from its subordinates and performs another PCA to select the second-level common factors. This process is repeated until the central server is reached, which collects factors from its direct subordinates and performs a final PCA to select the global common factors. The noise terms of the second-level approximate factor model are the unique common factors of the first-level clusters. We focus on the case of two levels in our theoretical derivations, but the idea can easily be generalized to any finite number of hierarchies, and the proposed method is also applicable to data with heterogeneous and multilevel subcluster structures that are stored and analyzed by a single machine. We introduce a new diffusion index approach to forecasting based on the global and group-specific factors. Some clustering methods are discussed when the group memberships are unknown. We further extend the analysis to unit-root nonstationary time series. Asymptotic properties of the proposed method are derived for the diverging dimension of the data in each computing unit and the sample size T. We use both simulated and real examples to assess the performance of the proposed method in finite samples, and compare our method with the commonly used ones in the literature concerning the forecasting ability of extracted factors.
报告人介绍：
高照省，浙江大学数据科学研究中心“百人计划”研究员，博士生导师。2016年于香港科技大学数学系获得哲学博士学位，先后于2016-2017年在英国伦敦政治经济学院和2017-2019年在美国芝加哥大学布斯商学院从事博士后研究工作。回国前于2019-2021年任职于美国理海大学数学系担任助理教授。研究方向主要集中在经济和金融市场中的数据分析方法，高维和大尺度统计和时间序列数据的统计分析，因子学习以及金融资产定价模型。研究成果发表在 《Journal of the American Statistical Association》《Journal of Econometrics》《International Journal of Forecasting》《Statistica Sinica》和《Econometrics and Statistics》等统计学和经济学杂志上。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/7ThNhchH
8、秋学期第七周讲座二
报告题目：变步长BDF格式的稳定性与收敛性
报告信息来源：https://math.sjtu.edu.cn/Default/index【上海交通大学数学科学学院学术报告】
报告人 Speaker：廖鸿林（南京航空航天大学)
时间 Datetime : 2022-10-27 上午 9:00-12:00
地点 Venue : 腾讯会议 ID: 937-340-801
报告摘要 Abstract :
我们把经典BDF公式看成一类非局部卷积逼近，借助于一个新的离散分析工具--离散正交卷积核，考察了变步长BDF格式的稳定性和L2模收敛性。新的稳定性结果合理地模拟了连续问题的稳定不等式，相应误差估计几乎不依赖步长比参数。这充分表明BDF格式对步长变化具有很强的鲁棒性，本质上改进了这个常用刚性求解器沿用四十年的稳定性结果。我们也考虑了高阶BDF格式，并将新分析方法应用到若干非线性相场模型，得到了一些新的理论结果。
报告人介绍：
廖洪林，应用数学博士，2018年至今任教于南京航空航天大学数学学院。2001年在解放军理工大学获理学硕士学位，2010年在东南大学获理学博士学位，2001-2017年任教于解放军理工大学。学术研究方向为偏微分积分方程数值解，目前主要关注相场以及多相流模型的时间变步长离散与自适应算法, 在Math Comp，SIAM J Numer Anal, SIAM J Sci Comput，IMA J Numer Anal，J Comput Phys, Sci China Math等国内外专业期刊上发表学术研究论文三十余篇。
报告链接：https://form.zju.edu.cn/#/dform/genericForm/g5f5GIPL
7、秋学期第七周讲座一
报告题目：Stable capillary CMC hypersurfaces and the second Robin eigenvalue
报告信息来源：浙江大学数学科学学院学术报告
报告人 Speaker：夏超（厦门大学)
时间 Datetime : 2022-10-25 上午10:00-12:00
地点 Venue : 腾讯会议ID: 880-635-181 密码: 1025
报告摘要 Abstract :
In this talk, we study stability of capillary CMC hypersurfaces. We provethat a capillary CMC hypersurface in a geodesic ball in space forms or a horoball inhyperbolic space is stable if and only if it is umbilical. In particular, the relationshipbetween the stability problem and the estimate for the second Robin eigenvalue of theJacobi operator will be mentioned.This is based on the joint work with Jinyu Guo andGuofang Wang.
报告人介绍：
夏超，厦门大学教授、博导，福建省闽江学者。主要研究领域是几何分析与非线性偏微分方程，在相关领域做出一系列有影响力的工作，成果发表在J. Differential Geom.,，Arch.Ration. Mech. Anal.，Adv. Math.，Math. Ann.,Trans.AMS等一流国际期刊上。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/es9J9RDw
6、秋学期第六周讲座一
报告题目：Estimating Optimal Infinite Horizon Dynamic Treatment Regimes via pT-Learning
报告信息来源：http://cds.zju.edu.cn 【浙江大学数学科学研究中心学术报告】
报告人 Speaker：周文卓 （University of California Irvine）
时间 Datetime :2022-10-21 上午10:00
地点 Venue :腾讯会议
备注 Remarks：会议号：230-614-982
报告摘要 Abstract :
Recent advances in mobile health (mHealth) technology provide an effective way to monitor individuals' health statuses and deliver just-in-time personalized interventions. However, the practical use of mHealth technology raises unique challenges to existing methodologies on learning an optimal dynamic treatment regime. Many mHealth applications involve decision-making with large numbers of intervention options and under an infinite time horizon setting where the number of decision stages diverges to infinity. In addition, temporary medication shortages may cause optimal treatments to be unavailable, while it is unclear what alternatives can be used. To address these challenges, we propose a Proximal Temporal consistency Learning (pT-Learning) framework to estimate an optimal regime that is adaptively adjusted between deterministic and stochastic sparse policy models. The resulting minimax estimator avoids the double sampling issue in the existing algorithms. It can be further simplified and can easily incorporate off-policy data without mismatched distribution corrections. We study theoretical properties of the sparse policy and establish finite-sample bounds on the excess risk and performance error. The proposed method is implemented by our proximalDTR package and is evaluated through extensive simulation studies and the OhioT1DM mHealth dataset. This is a joint work with Prof. Ruoqing Zhu and Prof. Annie Qu.
报告人介绍：
Wenzhuo Zhou is a postdoctoral fellow in Statistics at the University of California Irvine, where he works with Professors Annie Qu and Babak Shahbaba. Prior to that, He got the Ph.D. in Statistics from the University of Illinois Urbana Champaign in 2022, advised by Professor Ruoqing Zhu. His research mainly focuses on the reinforcement learning, dynamic treatment regimes, and natural language processing. His works have been published in some statistical journals, including Journal of the American Statistical Association, Biometrika, etc.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/vxMSmU07
5、秋学期第五周讲座三
报告题目：AI for Science
时间 Datetime : 2022-10-17 16:00-17:00
地点 Venue : 数学科学学院学术报告厅（海纳苑2幢2楼报告厅）
报告人 Speaker : 鄂维南 （中国科学院院士）
报告摘要 Abstract :
AI for Science 是一种新的科研范式。它不仅仅会带来科研效率的大幅度提高，帮助我们攻克许多过去难以解决的困难问题，也会改变现有的科研体系。尤其重要的是，它还将帮助开拓工业制造的新业态。在这个新的形势下，我们应该如何建立新的科研基础设施？如何选择课题、组建团队、确定目标？有哪些新的方向值得我们关注？哪些方面应该尽早布局？这个报告将就这些问题提出一些建议。
报告人介绍：
鄂维南，中国科学院院士，2022年国际数学家大会一小时大会报告人，2022年国际机器学习大会特邀报告人，北京大学国际机器学习研究中心主任，北京科学智能研究院（AI for Science Institute, Beijing）院长，北京大数据研究院院长，美国数学学会会士，美国工业与应用数学学会会士。主要从事计算数学、应用数学、机器学习及其在力学、物理、化学和材料科学等领域中的应用等方面的研究，在应用数学和科学计算的相关领域做出了突破性贡献。曾获首届美国总统青年科学家与工程师奖(1996)，冯康科学计算奖（1999），国际工业与应用数学联合会Collatz奖（2003），美国工业与应用数学学会 Kleinman 奖（2009），美国工业与应用数学学会 Theodore von Karman 奖（2014），美国工业与应用数学学会和 ETH 共同颁发的Peter Henrici奖（2019），ACM Gordon Bell 奖（2020），国际工业与应用数学联合会Maxwell奖（2022），2022年受邀在国际数学家大会作一小时大会报告。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/hihPMjyi （请同时在大群内转发的报告推文链接报名！此处链接仅为签到用）
4、秋学期第五周讲座二
报告题目：与算子相关的平方函数的交换子的紧性问题
报告信息来源：https://math.fudan.edu.cn/0a/69/c30472a461417/page.htm【复旦大学数学科学学院学术报告】
报告人 Speaker：薛庆营 教授(北京师范大学）
时间 Datetime :2022-10-14 15:30--16:30
地点 Venue :腾讯会议
备注 Remarks：会议号：879-967-650
报告摘要 Abstract :
算子的紧性问题是调和分析中一个重要问题，我们将对紧性问题的发展做一下回顾，主要介绍我们近期的关于带薛定谔算子的平方函数，包括g函数和Marcinkiewicz积分的交换子，以及带B-R平均的Stein平方函数的交换子的紧性的结果.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/aGadYuyO
3、秋学期第五周讲座一
报告题目：Global stability and non-vanishing vacuum states of 3D compressible Navier-Stokes equations
报告信息来源：https://math.sjtu.edu.cn 【上海交通大学数学科学学院学术报告】
时间 Datetime : 2022-10-11 16:00--17:00
地点 Venue : 腾讯会议
报告人 Speaker : Yao Lei （Northwest University, China）
备注 Remarks: 会议号 615552967 密码:221011
报告摘要 Abstract :
We investigate global stability and non-vanishing vacuum states of large solutions to the compressible Navier-Stokes equations on the torus , and the main purpose of this work is three-fold:
(1) Under the assumption that the density ρ(x,t) verifies sup_{t\geq 0} ||ρ(x,t)||_{L^{\infty}}<M, it is shown that the solutions converge to equilibrium state exponentially in -norm. In contrast to the previous related works where the density has uniform positive lower and upper bounds, this gives the first stability result for large strong solutions of the 3D compressible Navier-Stokes equations in the presence of vacuum.
(2) By employing some new thoughts, we also show that the density converges to its equilibrium state exponentially in L^{\infty}-norm if additionally the initial density ρ_0(x) satisfies
inf_{x \in T^3}||ρ_0(\cdot)||_{L^{\infty}} \geq c_0>0 .
(3) We prove that the vacuum state will persist for any time provided that the initial density contains vacuum, which is different from the previous work of [H. L. Li et al., Commun. Math. Phys., 281 (2008), 401-444], where the authors showed that any vacuum state must vanish within finite time for the free boundary problem of the 1D compressible Navier-Stokes equations with density-dependent viscosity μ(ρ)=ρ^{α} with α>1/2.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/FdZ6vWRO
2、秋学期第三周讲座二
报告题目：MATRIX KENDALL'S TAU IN HIGH-DIMENSIONS: A ROBUST STATISTIC FOR MATRIX FACTOR MODEL
报告信息来源：http://cds.zju.edu.cn 【浙江大学数学科学研究中心学术报告】
时间 Datetime : 2022-09-30 上午 10:00 开始
地点 Venue : 腾讯会议
报告人 Speaker : 何勇（山东大学金融研究院研究员）
备注 Remarks: 会议号 797-591-599
报告摘要 Abstract :
In this article, we first propose generalized row/column matrix Kendall's tau for matrix-variate observations that are ubiquitous in areas such as finance and medical imaging. For a random matrix following a matrix-variate elliptically contoured distribution, we show that the eigenspaces of the proposed row/column matrix Kendall's tau coincide with those of the row/column scatter matrix respectively, with the same descending order of the eigenvalues. We perform eigenvalue decomposition to the generalized row/column matrix Kendall's tau for recovering the loading spaces of the matrix factor model. We also propose to estimate the pair of the factor numbers by exploiting the eigenvalue-ratios of the row/column matrix Kendall's tau. Theoretically, we derive the convergence rates of the estimators for loading spaces, factor scores and common components, and prove the consistency of the estimators for the factor numbers without any moment constraints on the idiosyncratic errors. Thorough simulation studies are conducted to show the higher degree of robustness of the proposed estimators over the existing ones. Analysis of a financial dataset of asset returns and a medical imaging dataset associated with COVID-19 illustrate the empirical usefulness of the proposed method. This is a joint work with Yalin Wang, Long Yu, Wang Zhou and Wen-Xin Zhou.
报告人介绍:
何勇，山东大学金融研究院，研究员，山东大学未来青年学者；山东大学学士（2012），复旦大学博士（2017），师从张新生教授；从事金融计量统计、生物统计以及机器学习等方面的研究，在国际计量及统计学权威期刊Journal of Econometrics, Journal of Business and Economic Statistics, Biometrics, Biostatistics, Statistics in Medicine, Journal of Multivariate Analysis、中国科学：数学等发表研究论文30余篇；主持国家自然科学基金面上项目、青年基金，全国统计科学研究重点项目等，获第一届统计科学技术进步奖（第二位）。担任美国数学评论评论员，及JRSSB, JRSSC, Biometrics, EJS, SINICA等十余个国际知名学术期刊匿名审稿人。
报名链接：https://form.zju.edu.cn/#/dform/genericForm/cZgD4ZUt
签到名单：
学术讲座报名与签到表（9.30）.xls
1、秋学期第三周讲座一
报告题目：Energy-Conserving Discontinuous Galerkin Methods for Vlasov Systems
报告信息来源：https://math.sjtu.edu.cn 【上海交通大学数学科学学院学术报告】
时间 Datetime : 2022-09-28 16:00--17:00
地点 Venue : 腾讯会议
报告人 Speaker : 仲杏慧（浙江大学）
备注 Remarks: 会议号 221449855 密码 105738
报告摘要 Abstract :
We propose energy-conserving numerical schemes for the Vlasov-type systems. Those equations are fundamental models in the simulation of plasma physics. The total energy is an important physical quantity that is conserved by those models. Our methods are the first Eulerian solver that can preserve fully discrete total energy conservation. The main features of our methods include energy-conservative temporal and spatial discretization. In particular, an energy-conserving operator splitting is proposed to enable efficient calculation of fully implicit methods. We validate our schemes by rigorous derivations and benchmark numerical examples.
报名链接：https://form.zju.edu.cn/#/dform/genericForm/Ug5SSf0q