Computational Mathematics
About
Our research group is interested in various Computational Mathematics including high performance computing, PDE-constrained optimization, numerical optimization, image processing, deep learning techniques, computer modelling, pattern recognition, natural language processing (NLP), mathematics education and artificial Intelligence (AI).
Research themes
Our research studies how to apply numerical techniques to solve advanced computation problems with supercomputer and computer cluster.
Our research focuses on how to simulate and study complex systems using mathematics, physics, and computers.
Our group studies several techniques to process digital images such as object detection, pattern recognition and handwriting recognition.
In this area, we focus on the interactions between computers and human language.
Related programs
High performance computing and computational modeling are closely linked to BSc Industrial Mathematics and BSc Mathematics programs, especially in the courses related to Computer Simulation, Simulation Modelling and Data Structures and Algorithms to simulate the model.
Image processing and Natural language processing relates to several courses in other programs such as Linear Algebra, Introduction to data science and Mathematics for AI which use machine learning algorithms to apply with the problems of image processing.
Recent publications
Efficient numerical technique for solving integral equations
Navarasuchitr I, Huabsomboon P, Kaneko H
Thai Journal of Mathematics, 2021
A numerical study of oil spill prediction in the Gulf of Thailand using ocean wave model
Sriwichien S, Chayantrakom K, Kanbua W
Advances in Difference Equations, 2019
A numerical study of oil spill spreading in the Gulf of Thailand
Srikhaetai K, Chayantrakom K, Kanbua W
Advances in Difference Equations, 2019
Application of a deep learning technique to the problem of oil spreading in the Gulf of Thailand
Khlongkhoi P, Chayantrakom K, Kanbua W
Advances in Difference Equations, 2019
Stock market movement prediction using LDA-online learning model
Tantisripreecha T, Soonthomphisaj N
19th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2018
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