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加拿大Alberta数学与统计系黄友书教授学术报告通知
发布时间 : 2017-06-21     点击量:

        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:

        题目:Data sciences and its applications to real world problems

        时间:2017年6月26日下午4:00-6:00

        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

        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

        欢迎感兴趣的师生参加!

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