Education of Ko Yamasaki
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This article is an todo. It will be expanded only with confirmed details.
Education of Ko Yamasaki describes Ko Yamasaki's schooling, his gradual interest in information science, and his path toward graduate study.
His interest in computer science and artificial intelligence did not begin suddenly at university. It developed from a broader childhood and teenage interest in devices, the internet, technology news, and artificial intelligence.
Early education[edit]
In elementary school, Yamasaki encountered digital technology through games, YouTube, and electronic devices.
He did not yet have a clear plan to specialize in computer science, but he showed strong interest in new devices and services. Around the fifth grade, he reportedly wanted the MOVERIO smart glasses as a Christmas present, a detail later treated as evidence of early curiosity toward emerging technology.
By middle school, he was watching not only game-related videos but also discussion content about social issues and technology. This contributed to an interest in people with specialized knowledge.
For the main biographical article, see Ko Yamasaki.
High school[edit]
At a high-school entrance interview, Yamasaki recalls naming artificial intelligence as a field of interest.
At the time, AI systems competing with top players in games such as Go and shogi were widely covered in the news. Artificial intelligence was becoming visible even outside specialist communities.
High school life itself, however, was dominated by Rugby. Yamasaki played for three years, served as forward captain, and became vice-captain of the team. He did not study programming or machine learning in depth until entering university.
Hiroshima City University[edit]
After high school, Yamasaki entered the Faculty of Information Sciences at Hiroshima City University.
His university choice was influenced by the results of the Common Test for University Admissions and by realistic admission prospects. At the same time, the presence of an intelligent-systems course was an important attraction, since it allowed him to study artificial intelligence from the second year onward.
He studied machine learning, pattern recognition, image processing, algorithms, linear algebra, calculus, probability, and statistics, while gaining programming experience in Python, Java, coursework, and independent projects.
Artificial intelligence study[edit]
When Yamasaki began learning Machine learning, he was especially interested in how relatively simple mathematical models could infer relationships from data.
Even linear regression felt striking because the model estimated structure from examples. As his study continued, he became interested in the way machine learning combines linear algebra, calculus, probability, statistics, and optimization.
Coursework also introduced image recognition, neural networks, reinforcement learning, and generative models.
Undergraduate research[edit]
His undergraduate research concerns pattern discovery and learning over tree-structured data.
He became interested in unordered trees and tree patterns with variables, both of which are difficult to represent as ordinary tabular data. This experience later connected to his interest in Graph neural networks and graph-structured machine learning.
Graduate school[edit]
Yamasaki chose graduate school in order to continue studying information science and machine learning.
In 2026 he passed entrance examinations for Tokyo Institute of Science and the University of Tsukuba. He chose Tokyo Institute of Science and is scheduled to begin graduate research there in April 2027.
His planned interests include GNNs, XAI, graph representation learning, and the extension of his undergraduate work on structured data.