学术报告一
报告题目: Modeling animal movement with memory with partial differential equations with time-delay
报 告 人： 史峻平 教授 （美国威廉玛丽学院）
报告时间：2018年6月10日（星期日）下午15：00-16：00
报告地点：星际电子在线学术报告厅（25教14楼）
参加人员：教师、研究生、本科生
Abstract
Animal populations often self-organize into territorial structure from movements and interactions of individual animals. Memory is one of cognitive processes that may affect the movement and navigation of the animals. We will review several mathematical approaches of animal spatial movements, and also introduce our recent work using partial differential equations with time-delay to model and simulate the memory-based movement. We will show the bifurcation and pattern formation for such models.
个人简介：史峻平，美国威廉玛丽学院(College of William and Mary)汉密尔顿讲座教授。1990-93年南开大学学习，1998年毕业于美国杨百翰大学，获博士学位。主要研究方向为偏微分方程，动力系统，分歧理论，非线性泛函分析，生物数学。在偏微分方程，分歧理论方面的研究工作受到国际上广泛重视。另外在生物数学，包括种群模型，生物化学反应，形态生成，生态系统稳定性等方面都有研究。曾任哈尔滨师范大学龙江学者讲座教授，主持参加美国和中国国家科学基金会基金项目多项，主持组织国际学术会议20多次，在国际学术会议做大会报告/邀请报告100余次。担任多个国际知名SCI刊物编委，为60多种数学、物理、生物刊物审稿人。发表学术论文150余篇，其中被SCI收录140余篇，被SCI杂志引用1700余次（它引1200余次）。
学术报告二
报告题目: On impulsive reaction-diffusion-advection models in higher dimensions
报 告 人： 王皓 教授（加拿大阿尔伯塔大学）
报告时间：2018年6月10日（星期日）下午16：00-17：00
报告地点：星际电子在线学术报告厅（25教14楼）
参加人员：教师、研究生、本科生
Abstract
We formulate a general impulsive reaction-diffusion-advection equation model to describe the population dynamics of species with distinct reproductive and dispersal stages. The seasonal reproduction is modeled by a discrete-time map, while the dispersal is modeled by a reaction-diffusion-advection partial differential equation. Study of this model requires a simultaneous analysis of the differential equation and the recurrence relation. When boundary conditions are hostile we provide critical domain results showing how extinction versus persistence of the species arises, depending on the size and geometry of the domain. We show that there exists an extreme volume size such that if the region size falls below this size the species is driven extinct, regardless of the geometry of the domain. To construct such extreme volume sizes and critical domain sizes, we apply the classical Rayleigh-Faber-Krahn inequality and the spectrum of uniformly elliptic operators. The critical domain results provide qualitative insight regarding long-term dynamics for the model. Last, we provide applications of our main results to certain biological reaction-diffusion models regarding marine reserve, terrestrial reserve, insect pest outbreak, and population subject to climate change.
个人简介：王皓, Dr. Hao Wang is currently a tenured faculty member at the University of Alberta. His research has been funded by NSERC, MITACS, OSRIN, PIMS, and the Province of Alberta. He has supervised more than 20 trainees at all levels, including 3 PDFs. He received the Early Career Award from MBI (United States) in 2013. He is an editor/associate editor/regional editor for several journals in United States and Europe.
Dr. Wang’s research program is truly interdisciplinary at the interface of mathematical, computational, and experimental studies. His research focuses on differential equations and their applications in life sciences. Via multiscale modeling (multiple scales of time and/or space), he has fulfilled many significant research accomplishments in the areas of stoichiometric modeling, microbiology, ecotoxicology, species invasions, and infectious diseases. His research group actively collaborates with biologists, engineers, industrial partners and governments, to explore and resolve urgent environmental problems. Many of his mathematical models are tested and calibrated by laboratory and/or field experiments. At the University of Alberta, Dr. Wang is leading several interdisciplinary modeling projects on estimation and reduction of greenhouse gas emissions from biodegradation in oil sands industry, impacts of industrial toxins on ecosystems using the stoichiometric approach, control of invasive species in North America, spatial modeling of animal movements, and transmission of infectious disease using an inverse method and fully controlled fish-based lab experiments.
