FACULTY
SHINICHIRO SHIROTA
Graduate School of Social Data Science/Associate Professor
Field of Study
Bayesian Statistics
Spatial/Spatio-temporal Statistics
Computational Statistics
INTERVIEW
Unique Appeal of the Social Data Science Program
SDS is a new faculty to be established in 2023. It is the first faculty in Japan to focus on the crossover between social science and data science, and will offer a full range of data science and social science courses. The department offers a more practical education through a variety of experiences such as exercises, internships at companies, and research.
As for research, we believe that there are still many unexplored areas left to be explored in the social science and data science fields. We also have opportunities for joint research with companies, which gives us the chance to find research themes that are relevant to the real world.
I believe that data science in the social sciences tends to be more about soft skills such as management and networking, rather than simply technical skills. In such a field, not only data science skills but also knowledge in the social sciences are important, so I consider the environment at SDS to be attractive, where students can learn both types of knowledge in parallel.
As for research, we believe that there are still many unexplored areas left to be explored in the social science and data science fields. We also have opportunities for joint research with companies, which gives us the chance to find research themes that are relevant to the real world.
I believe that data science in the social sciences tends to be more about soft skills such as management and networking, rather than simply technical skills. In such a field, not only data science skills but also knowledge in the social sciences are important, so I consider the environment at SDS to be attractive, where students can learn both types of knowledge in parallel.
Innovative education and research encouraged in the Social Data Science Program
It is difficult for social science departments to provide sufficient statistics courses due to constraints such as the number of faculty members and the number of classes. SDS offers a wide range of social science courses along with a full range of statistics and AI courses, We believe that this enables more practical education.
Statistics is a field that has developed along with its applications. Therefore, collaboration with applied fields in academia has been active. In addition to this, in recent years, with the increase in the number of data scientists in industry, opportunities for collaborative research with companies have also increased. In addition to research in statistical methodology, we hope to uncover new seeds of research through such collaborations and link them to joint research.
Statistics is a field that has developed along with its applications. Therefore, collaboration with applied fields in academia has been active. In addition to this, in recent years, with the increase in the number of data scientists in industry, opportunities for collaborative research with companies have also increased. In addition to research in statistical methodology, we hope to uncover new seeds of research through such collaborations and link them to joint research.
CLASS
- (U)Bayesian Statistics 1
- (U)Bayesian Statistics 2
- (U)Project-Based Learning Reserch B
- (G)Social and Economic Analysis by Spatial Information
RESEARCH
Research Website
Our research is based on the two pillars of Bayesian statistics and spatial statistics. Bayesian statistics is a field that is not usually taught in the basic statistics that you learn in undergraduate courses. It is one of the fundamental technologies for AI and is a very important field. Our research focuses on estimation and model development for stochastic processes such as Gaussian processes based on modeling techniques such as hierarchical Bayesian and state space models.
Keywords
- Bayesian Statistics
- Spatial/Spatio-temporal Statistics
- Computational Statistics