Various climate-change related risks such as disasters, water and food shortage, etc. are mainly concentrated in urban areas. In particular, social infrastructure contributing to urban risk mitigation is not in place in most informal settlements (i.e., slums), where about 30% of the world’s urban population live. On the other hand, partially because population inflows from surrounding rural areas lead to further expansion of informal settlements, it is important to support not only urban development, but also rural development at the same time.

These urban and rural issues are one of the central issues to be resolved towards achieving “Sustainable Development Goals (SDGs)” presented at the UN Sustainable Development Summit in 2015. Although various countermeasures have been discussed by practitioners and researchers across disciplines and fields, there are still many challenges for better policy decisions. First, there is a great lack of understanding on the preferences and behavior of residents who live in disadvantaged areas where social infrastructure is not well developed. There are a number of cases where policy judgment based on the “stereotype” understanding has resulted in worsening the situation. Second, there is a growing possibility to install next generation smart infrastructure, which can be inexpensive and efficient. In particular, it is required to utilize appropriate technologies tailored to the problems of each region, rather than a uniform introduction of advanced technologies which tends to become overqualified.

Given the above concerns, “Infrastructure Planning and Urban Risk Management Laboratory”, under the Graduate School for International Development and Cooperation, is currently studying on the reduction of poverty and disaster risk in urban informal settlements, social implementation of next generation infrastructure in disadvantaged areas, and evaluating the impacts of smart infrastructure. Our research interests span a wide range of disciplines and we emphasize cross-disciplinary and quantitative approaches, while the conceptual/theoretical foundation underlying and underpinning our works is human behavior modeling. For theories/methodologies, we are particularly interested in:

* Activity-travel behavior analysis
* Causal inference
* Big data analysis
* Infrastructure system design

Based on these theories/methodologies, we have been doing research (1) for a better understanding of activity-travel behavior of the people who live in disadvantaged areas including slums in Mumbai, disaster prone areas of Bangladesh, and rural areas in Japan, (2) to assess the social impacts of urban and transportation infrastructure development in cities in developing countries including India, Vietnam, and Indonesia, (3) to explore the possibility of introducing new infrastructure system such as automatic driving system and mobility sharing services.

Infrastructure planning is usually considered as one branch of Engineering, but we believe it is more than that: it would contribute to the alleviation of conflicts caused by disadvantaged conditions and thus it is a part of peace studies in a broad sense. We would like to continue our research without losing such fundamental social value of infrastructure.

We particularly welcome students who are interested in the development of the theory and methodology concerning activity-travel behavior, have a strong interest in appropriate social implementation of new technologies, and who want to contribute to solving problems in disadvantaged areas.






  • 生活・交通行動分析手法
  • 統計的因果推論
  • 各種ビッグデータの解析
  • インフラシステムのデザイン