Hiroaki Sasakiassociate professor

(university) degree

PhD (Engineering)

field of research

statistical machine learning

Research Keywords

Research

Statistical machine learning is one of the fundamental research fields of modern artificial intelligence, which aims to build methods for computers to learn useful knowledge, information and rules hidden in large amounts of data. In previous research, we have not only proposed various machine learning methods based on mathematical foundations, but also analysed these proposed methods theoretically. Other research interests include the application of machine learning methods to real-world and real-society applications.

Possible graduation research topics.

'Making' machine learning methods: construction and theoretical analysis of machine learning methods. For example,

• Building machine learning methods for complex data domains.
• Proposed machine learning methods robust to data outliers.
• Theoretical analysis of existing and proposed machine learning methods, etc.

'Using' machine learning methods: application of machine learning methods to real problems. Example,

• Development of prediction systems using machine learning methods.
• Analysis and use of word of mouth and sports data

Hobbies, skills and likes

Watching sports (especially rugby, basketball and football)

Message to candidates and students

Mathematical science is one of the foundations of information technology, and my research field, machine learning, is also rooted in mathematical science. Young researchers are active worldwide in machine learning, and flexible conceptual skills are needed. So, why don't you express your flexible conceptual skills using mathematics and realise them on a computer? I am sure that you will have unexpected flashes of inspiration and moments of discovery in the process of this challenge, which will surely be an important experience.