معرفی
Tota Suko is an Associate Professor at the School of Social Sciences, Waseda University, specializing in statistical learning theory and business analytics. With a Ph.D. in Engineering from Waseda University, Dr. Suko leads the Suko Seminar (Management Science Seminar) where students learn to solve business problems using mathematical and management science approaches, primarily through data science techniques including statistical analysis and machine learning.
Dr. Suko's research spans multiple domains in statistics and data science. His primary interests include Bayesian statistics, statistical learning theory, business statistics, data mining, and information theory. He has developed methods for analyzing survey data with selection bias, detecting poor responses in questionnaires, and parameter estimation in regression models. His work bridges theoretical statistics with practical applications in business analytics, e-commerce, and even nanotechnology through collaborations with physics researchers.
Dr. Suko's recent publications demonstrate a strong trend toward practical applications of statistical methods. His work on generative AI for criminal case law analysis shows innovative application of AI in legal domains, while his research on questionnaire quality control addresses fundamental issues in survey methodology. He has also made significant contributions to theoretical aspects of statistical learning, particularly in the areas of label noise, selection bias, and parameter estimation under non-ideal data conditions.
- Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research projects
- Waseda Data Science Consortium industry-academia collaborations
- Research on nanoscale semiconductor prediction models
- Development of methods for low-quality data analysis
Dr. Suko actively supervises both undergraduate and graduate students through the Suko Seminar. Students work on individual or team projects, participate in data analysis competitions, and present their research at academic conferences. He has developed educational approaches including full-on-demand content for data science education and modularized online statistical teaching materials.
Dr. Suko leads the Suko Seminar (Management Science Seminar), which actively collaborates with companies and research institutions. His research team works on diverse projects including analysis of purchasing and browsing histories on e-commerce sites, prediction modeling for nanoscale conduction, and development of methods for low-quality data analysis. The seminar emphasizes both theoretical understanding and practical application of data science techniques to solve real-world business problems.