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Professor Pang Mingyong of Nanjing Normal University: from numerical approximation to manifold learning

PostBy: 本科生    addtime: 2019-12-15 18:32:00   hit:

News from School of Educational Information Technology:

At 14:30 on November 29, 2019, professor Pang Mingyong of Instructional Technology of Nanjing Normal University delivered an academic report from numerical approximation to manifold learning for the teachers and students of our college in 9638. The seminar was presided over by teacher Wei Yantao.

The report mainly consists of four parts: numerical approximation, machine learning, dimensional reduction of multidimensional data and parameterization. Professor Pang simply introduced the numerical approximation method, data fitting method, approximation function and neural network learning, shared the current numerical approximation problems, entanglements and important findings, and cited practical application cases such as image aspect ratio optimization and plane projectile system.

Through this seminar, the teachers and students of our college have a deeper understanding of the related research from numerical approximation to manifold learning. It plays a positive role in promoting the improvement of our college's scientific research level in the future.

About the speaker:

He is the professor and doctoral supervisor of Instructional Technology, in the Nanjing Normal University. He is a standing member of CAD/CG committee of Jiangsu Computer Society and Jiangsu Association for the Application of Microcomputer Multimedia and its Application Technology Professional Committee. He is devoted to the research of 3D digital model modeling technology and related processing algorithms. He has presided over or participated in 6 projects of National Natural Science Foundation, nearly 20 provincial / ministerial level, and more than 10 horizontal commissioned projects. In recent years, he has published more than 150 academic papers in domestic core journals, international conferences or international journals, among which more than 100 papers have been included in EV/SCI/STP.