On 7 October 2026, the Railway Engineering and Technology Programme, through the Automotive and Transportation Technology Center (ATTC), School of Engineering, University of Phayao, in collaboration with Ascendas Systems Co., Ltd., organised an academic training workshop entitled “MATLAB | GenAI / Agentic AI Workflows and What’s New in R2026b” at Computer Laboratory EN 1301. The workshop aimed to enhance participants’ knowledge and practical proficiency in MATLAB while promoting the integration of artificial intelligence (AI) technologies into teaching and learning, engineering practice, and academic research.
The workshop featured Mr. Phudis Sombatsirinan, a PhD student at the Research School of Earth Sciences, Australian National University, and Mr. Phudis Sombatsirinan, Representative of Ascendas Systems Co., Ltd., who served as the guest speaker. He shared his expertise and practical insights with academic staff, students, researchers, and other interested participants. The training programme covered four principal topics:
Introduction to MATLAB: An overview of MATLAB fundamentals, essential functionalities, and practical approaches to using the software for computational and engineering applications.
GenAI and Agentic AI Workflows with MATLAB: An exploration of how generative artificial intelligence (GenAI) and agentic AI can be integrated into MATLAB-based workflows to support engineering tasks, computational processes, and research activities.
What’s New in MATLAB R2026b: An introduction to the latest features, enhancements, and capabilities introduced in MATLAB R2026b, highlighting their potential applications in engineering and scientific computing.
MATLAB for Data Analytics: An examination of MATLAB-based approaches to data processing, analysis, and interpretation, with an emphasis on supporting engineering applications and research-driven decision-making.
The initiative underscored the School of Engineering, University of Phayao’s commitment to strengthening collaboration with the private sector to enhance the professional competencies and technological readiness of its academic staff and students. By fostering expertise in advanced computational tools and emerging AI technologies, the workshop sought to equip participants with the knowledge and skills required to adapt to rapid technological advancements.
Furthermore, the training contributed to the School’s broader efforts to strengthen engineering and research capabilities, encourage the practical application of artificial intelligence, and promote innovation aligned with evolving industrial demands and future technological developments.