Data sciences and its applications to real world problems

讲座名称: Data sciences and its applications to real world problems
讲座时间 2017-06-26
讲座地点 理科楼407
讲座人 黄友书
讲座内容

应数学与统计学院的邀请,加拿大Alberta数学与统计系黄友书教授将于近期访问我院,并为师生做以下学术报告:

报告题目:Data sciences and its applications to real world problems
报告时间:2017年6月26日下午4:00-6:00
报告地点:理科楼407
Abstract:With the rapid advances in computer and data storage technologies, massive data have now been routinely recorded in every sector ranging from science, engineering, medical research, business and social networking, etc. Although the technology enables us to collect and to process large amount of data at high frequency rate, we are still lagging a clear understanding of what is the best way to utilize the available data and how to extract important information and feature from the data set. It should be noted that in addition to artificial intelligent and machine learning, solid knowledge in mathematical and statistical sciences also play an important role in the study of data sciences and its applications to solve real world problems. In this presentation, I review our work on utilizing real data for three practical applications:
(1) Classification in toxicity assessment
(2) Prediction for nonlinear behaviour in aeroelastic systems
(3) Designing an intelligent sprinkler system
References:
[1]Machine learning algorithms for mode-of-action classification in toxicity assessment, in BioData Mining, 2016
[2]Structural Nonlinearity Identification and Steady-State Behavior Prediction from Transient Aeroelastic Data, presented at the NATO Specialists’ meeting inAdvanced Methods in Aeroelasticity,2008
 

讲座人介绍
报告人简介:
Education:
1. D. Phil. in Mathematics, Oxford University,England, 1978
2. M. Sc. in Mathematics, Oxford University,England, 1976
3. B. Sc. in Electrical Engineering, University of Southampton, 1975
Interests:
Applied Mathematics, Numerical Analysis and Sciences Computing, Solving Practical Problems in Sciences and Engineering, Computational Aerodynamics and Aeroelasticity, Nonlinear Dynamical System, Data Mining Tecniques
 

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