上海科技大学 | English | 地图
首页> 新闻信息> 活动
An Information Theoretic Approach to Computational Modeling in Engineering and the Sciences
Date:2016/10/10     Browse:641

Seminar Topic: An Information Theoretic Approach to Computational Modeling in Engineering and the Sciences

Speaker: Nicholas Zabaras (Viola D. Hank Professor of Aerospace and Mechanical Engineering, University of Notre Dame)
Time:   Oct. 10, 1:30 p.m. - 2:30 p.m.
Venue: Room 403, Teaching Center (Huanke Rd.)

Abstract:

The future of computational science and engineering is in many ways dictated by dramatic advances in data-intensive computing, growing use of imaging, sensors and feedback control systems in guiding simulations, widespread emphasis in `Big Data’, analysis of biological systems at the cellular level, dramatic progress in rapid prototyping and nano-manufacturing, and the need to quantify uncertainties in predictions. An emerging view is that computational science will require interdisciplinary approaches towards (a) models that bridge several spatial/temporal scales (Multiscale/Multiphysics Modeling), (b) models guided by high-dimensional data (Data-Driven Simulation), and (c) models that quantify our confidence in the predictions (Uncertainty Quantification). An interdisciplinary approach to these themes poses unique challenges in particular when the focus is on engineering and scientific applications (e.g. predictive materials science, climate modeling and environmental/geological sciences, systems biology, nanoscale device design, complex interconnected systems – from the power grid to aircraft engines, and other).

We will advocate an information theoretic approach to address these challenges. In particular, we will discuss data-driven models for uncertainty quantification, forward uncertainty propagation in high dimensions using limited data, variational approaches to stochastic coarse graining, quantifying epistemic uncertainty when using surrogate models and probabilistic graphical model based approaches for multiscale and multiphysics problems. Examples will be shown from diverse areas including quantification of uncertainties in ab initio thermodynamical properties of alloys to predictive modeling of polycrystalline materials.

Biography:

Prof. Nicholas Zabaras received his Diploma Degree in Mechanical Engineering at the National Technical University of Athens, Greece (1982), a M.S. in Materials at the University of Rochester, NY (1983) and PhD at Cornell University (1987) in Theoretical and Applied Mechanics. Upon receiving his Ph.D., he joined the faculty of Engineering at the University of Minnesota, Minneapolis, MN. Early research focused on the solution of inverse/design problems in the area of materials processing. In 1991, he returned to Cornell as a faculty of the Sibley School of Mechanical and Aerospace Engineering. At Cornell, he was also member of several other academic fields including Materials Science and Engineering, Applied Mathematics, Computational Science and Engineering. He was the founding director of the Materials Process Design and Control Laboratory (MPDC) that emphasized innovative materials modelling and design research with methodological approaches in mathematics, statistics and scientific computing. Particular areas with major contributions included inverse problems, uncertainty quantification and multiscale/multiphysics modelling.

Prof. Nicholas Zabaras joined Notre Dame's College of Engineering after serving as founding director of the Warwick Centre for Predictive Modeling at the University of Warwick and the Hans Fisher Senior Fellow with the Institute for Advanced Study at the Technical University of Munich.

Prof. Zabaras has received several awards for his work. They include a 1991 Presidential Young Investigator Award for his work on Inverse Problems. In 2014, he was appointed as Hans Fisher Senior Fellow at the Institute of Advanced Study at the Technical University of Munich for his work on uncertainty quantification. At the same year he received the Royal Society's Wolfson Research Merit Award. He is Fellow and member of several professional societies. He currently serves as the Associate Editor of the Journal of Computational Physics and as the Editor in Chief of the International Journal for Uncertainty Quantification.

Seminar 16073