From October 14 to 16, 2025, the Center of Excellence in Theoretical and Computational Science (TaCS-CoE), in collaboration with the Department of Mathematics, Faculty of Science, King Mongkut’s University of Technology Thonburi (KMUTT), organized the TaCS Mathematical Seminar Series No.18 on the topic “Control and Optimization via Machine Learning.” The seminar was held in collaboration with the CaRe Network and iDEAL–CoDE @CaRe Lab, with Prof. Dr. Poom Kumam, Head of TaCS-CoE, serving as the project leader and providing close academic guidance and support.
The seminar aimed to create a platform for exchanging knowledge and research ideas in Machine Learning and Optimization, focusing on their applications in Mathematical Control Systems and the enhancement of Learning Model efficiency. Throughout the three-day event, researchers and graduate students from various institutions, both domestic and international, actively participated. The sessions featured distinguished speakers from Naresuan University, including Prof. Dr. Rabian Wangkeeree, Assoc. Prof. Dr. Kasamsuk Ungchittrakool, and Dr. Yirga Abebe Belay (Postdoctoral Researcher). Their lectures covered both theoretical foundations and computational applications, ranging from the fundamentals of Support Vector Machines (SVM) to the connection between Convex Optimization with Neural Network, core elements driving the advancement of Artificial Intelligence (AI).
The workshop fostered a warm and collaborative atmosphere, where researchers exchanged deep academic perspectives and computational techniques. Discussions emphasized the development of new optimization methods to enhance model learning performance and bridge theoretical mathematics with real-world applications in advanced research. This event marks another successful milestone in fulfilling the mission of TaCS-CoE to “Bridge Mathematics and Intelligent Technologies”, strengthening Thailand’s research capabilities to reach international standards under the collaborative frameworks of the CaRe Network and iDEAL–CoDE @CaRe Lab.
