报告题目1：On the problem of spreading in Lotka-Volterra competition models
报告人：King-Yeung Lam (Adrian)
报告时间：08:30
报告内容简介:
I will report some recent progress on a Hamilton-Jacobi approach to determine spreading speed in reaction-diffusion systems involving more than one species. In contrast to the  previous method of constructing delicate pairs of super-subsolutions, the approach here   consists in obtaining large-deviation type estimates in certain moving coordinates y = x – ct, which is inspired by the Hamilton-Jacobi approach due to Freidlin, Evans and Souganidis. This approach enables a decoupling of the problem, and allows the determination of multiple spreading speeds in certain non-cooperative systems. This is   mostly joint work with Shuang Liu and Qian Liu (Renmin and Ohio State).
报告人简介：
King-Yeung Lam, 美国俄亥俄州立大学教授。2011年于美国明尼苏达大学获得博士学位，师从倪维明教授。在美国俄亥俄州立大学(OSU)先后为Mathematical Biosciences Institute 博士后、Zassenhaus助理教授、教授等。研究领域包含偏微分方程特别是抛物椭圆方程（组）和自由边界问题，及其在生物种群中的应用。已在“SIAM J. Appl. Math.”、“SIAM J. Math. Anal.”、“J. Differential Equations”、“Calc. Var. Partial Differential Equations”、“J. Funct. Anal.”、“Mem. Amer. Math. Soc.”、“Indiana Univ. Math. J.” “J. Math. Biol.”、“Bull. Math. Biol.”等国际著名SCI杂志上发表学术论文30多篇。

报告题目2：Concentration behavior of endemic equilibrium for a reaction-diffusion-advection SIS epidemic model with mass action infection mechanism
报告人：彭锐教授
报告时间：10:30
报告内容简介:
In this talk, I shall report our joint work on a reaction-diffusion-advection SIS epidemic model with mass action infection mechanism in a one dimensional bounded domain. We first prove the existence of endemic equilibrium (EE) whenever the basic reproduction number is greater than unity. We then focus on the asymptotic behavior of EE in three cases: large advection; small diffusion of the susceptible population; small diffusion of the infected population. Our main results show that the asymptotic profiles of the susceptible and infected populations obtained here are very different from that of the corresponding system without advection and that of the system with standard incidence infection mechanism. Thus, the effects of advection and different infection mechanisms are substantial on the spatial distribution of infectious disease; our findings bring novel insight into the disease control strategy. This talk is based on my joint work with Renhao Cui, Huicong Li and Maolin Zhou.
报告人简介：
彭锐，教授，江苏省特聘教授，入选“教育部新世纪优秀人才支持计划”，获得“江苏省杰出青年基金”和“江苏省数学成就奖”，入选江苏省“333人才工程”中青年学科带头人。博士毕业于东南大学和澳大利亚新英格兰大学，曾在加拿大纽芬兰大学AARMS和美国明尼苏达大学IMA（美国NSF资助）从事博士后工作,  德国“洪堡学者”获得者。彭锐目前的主要研究兴趣包括偏微分方程、动力系统理论以及在生物学、传染病学和化学反应等领域的应用。已在Transactions of the American Mathematical Society、Journal of Functional Analysis、SIAM Journal on Mathematical Analysis、Indiana University Mathematics Journal、Journal of Nonlinear Science、Calculus of Variations and Partial Differential Equations、SIAM Journal on Applied Mathematics、Journal of Mathematical Biology、Physica D、Nonlinearity、European Journal of Applied Mathematics、Journal of Differential Equations等数学杂志发表学术论文多篇。

报告题目3：Mathematical modeling about the scheduling of combination cancer therapy with immune checkpoint inhibitors
报告人：赖秀兰副教授
报告时间：14:30
报告内容简介:
There has been much progress in recent years in developing checkpoint inhibitors, primarily PD-1 antibodies and PD-L1 antibodies. However, because of lack of tumor-infiltrating effector T cells, many patients in clinical trials do not respond to checkpoint inhibitor treatment. It was recently suggested that the combination of an immune checkpoint inhibitor and another anti-tumor drug, such as a chemotherapy drug or radiotherapy, may function synergistically to induce more effective antitumor immune responses. The questions in the design of cancer clinical trials with combination of two drugs includes in which proportion (dosage) and in which order to administer the drugs. In this talk, I will address the scheduling question by mathematical modeling approaches. We considered the combination therapies of cancer with a checkpoint inhibitor and a cancer vaccine (or anti-VEGF) using mathematical models. We use mathematical models to explore the efficacy (synergistic or antagonistic) of the two drugs and the appropriate dosage and timing of the combination treatment.
报告人简介：
赖秀兰，中国人民大学数学科学研究院副教授，博士毕业于加拿大西安大略大学应用数学系，2014-2018年期间在中国人民大学数学科学研究院和美国俄亥俄州立大学生物数学所从事博士后研究，主要从事生物医学相关问题预测模型的模型建立、理论分析、数值模拟方面研究，包括关于癌症的数学建模，感染者体内病毒动力学研究。在PNAS, Science China Mathematics, SIAM Journal of Applied Math, Journal of Differential Equations, Journal of Theoretical Biology, BMC System Biology等核心期刊发表20余篇论文。作为课题负责人主持过一项国家自然科学基金项目。