Shonosuke Sugasawa - Appointed in AY2023
Participant Profile
Shonosuke Sugasawa
Statistical Science, Data Science, Econometrics2013: Graduated from the Faculty of Science and Technology, Keio University 2015: Completed the Master's Program at the Graduate School of Economics, The University of Tokyo 2018: Obtained a Dissertation Ph.D. from the Graduate School of Economics, The University of Tokyo After serving as a Project Researcher at the Institute of Statistical Mathematics and as a Lecturer and Associate Professor at the Center for Spatial Information Science, The University of Tokyo, he has held his current position since 2023.
Shonosuke Sugasawa
Statistical Science, Data Science, Econometrics2013: Graduated from the Faculty of Science and Technology, Keio University 2015: Completed the Master's Program at the Graduate School of Economics, The University of Tokyo 2018: Obtained a Dissertation Ph.D. from the Graduate School of Economics, The University of Tokyo After serving as a Project Researcher at the Institute of Statistical Mathematics and as a Lecturer and Associate Professor at the Center for Spatial Information Science, The University of Tokyo, he has held his current position since 2023.
The Ability to Statistically Analyze Data Is a Powerful Asset
Research Theme and How He Encountered It
My specialty is statistical science and data science. Based on challenges in actual data analysis, I conduct research on new statistical analysis methods under the motto of "making it possible to analyze what was previously unanalyzable." In particular, I focus on an approach called Bayesian statistics, conducting research that handles various types of data, such as data observed over time and location, and functional data. I also conduct applied research using statistical science in collaboration with researchers in related fields.
The first time I learned the fundamental theories of statistics was in my third year of university. As I was in the Department of Mathematics at the time, I focused mainly on the theoretical aspects. After entering graduate school, I encountered Bayesian statistics and became interested in its practical utility and convenience. Since then, I have pursued my research by studying implementation and algorithms in parallel with theory, focusing on the development and application of methodologies.
The Appeal and Interest of the Research Theme
I believe the interesting thing about statistical science and data science is their close connection to various applied fields. Furthermore, data analysis methods used in seemingly different fields (for example, economics and medical sciences) can sometimes be statistically similar. This means that the ideas behind analysis methods used in one field can potentially be applied to data analysis challenges in other, seemingly unrelated fields. I feel that the emergence of new ideas and insights from such an interdisciplinary perspective is the appeal of statistical science and data science.
Message to Students
The world is overflowing with all kinds of data. While the ability to analyze data using the power of statistical science and data science is important in itself, I believe it is also crucial to acquire an "intuition" and literacy for handling data by systematically learning the underlying theories.
Students in the Faculty of Economics at this university begin learning basic statistics from their first year. This is the gateway to statistical science and data science. If you are interested in data analysis techniques and their application in the real world, I think you will find it interesting to study more specialized content at the university or in graduate school.