报告题目：Bayesian Estimation and Applications in Nanotechnology and Tomography
报告人：    Prof.Clemens Heitzinger  奥地利维也纳科技大学
报告时间：2019年3月12日  周二9:30  
报告地点：中北校区数学馆201

报告摘要：
Bayesian estimation is a method to learn unknown features from data. In particular, we use computational Bayesian inversion based on PDE (partial differential equation) models as a machine-learning method in order to identify unknown parameters which correspond to physical or geometrical properties in various applications in nanotechnological sensors and tomography. Applications such as electrical-impedance tomography, nanoelectrode sensors, and nanowire field-effect sensors lead to deterministic and stochastic partial differential equations that model electrostatics and charge transport in these devices. The main model equations are the nonlinear Poisson-Boltzmann equation and the stochastic drift-diffusion-Poisson-Boltzmann system.The main question how as much information as possible can be extracted from measurements naturally arises next. We use computational Bayesian inversion to reconstruct physical and geometric parameters of the body interior in electrical-impedance tomography, of nanoelectrodes and the liquid in nanoelectrode sensors, and of nanowires and target molecules in nanowire field-effect sensors. The main advantages of computational Bayesian inversion is that it not only yields the unknown parameters whenever possible, but also their probability distributions and hence the uncertainties in the reconstructions, which is essential in the case of ill-posed inverse problems. In addition to showing the well-posedness of the Bayesian inversion problem for the nonlinear Poisson-Boltzmann equation, the numerical methods are presented and numerical results for the three applications such as multifrequency reconstruction for nanoelectrode sensors are shown.

报告人简介：
Heitzinger博士自2015年起，在奥地利维也纳科技大学数学与地理信息学院担任副教授，同时在美国亚利桑那州立大学数学与统计学院担任兼职教授。Heitzinger教授曾是美国亚利桑那州立大学访问学者，美国普渡大学电子与计算机工程学院副研究员，英国剑桥大学应用数学与理论物理学院高级副研究员。2013年Heitzinger教授荣获由奥地利联邦政府科学基金委颁发的START奖。该奖用于表彰在奥青年科学家的杰出科学贡献，在奥地利有卓越的影响力。Heitzinger 教授近 160 篇学术论文发表在国际高水平学术期刊与会议上，另著有教材“Algorithms in Julia”，将于 2019 年 7 月份由著名学术出版商 Springer 出版。