In order to create a sustainable society, it is necessary to reduce the impact on the global environment caused by the social actions of people and to develop a zero-emission society. Ecosocial System Engineering is a new discipline that crosses and integrates conventional disciplinary boundaries. Our goals are based on the three academic pillars: materials recycling, social system innovation, and mathematical model analysis of their systems. Students are expected to acquire the ability to think logically in handling problems generated by human activities and to attain adequate knowledge to be a competent engineer who will help the creation of a sustainable society.

Materials Recycling System

• Surface and interfaces science and Nanoengineering using scanning probe microscopy
• Analysis of algal substance concerning with light, Development of environmental technology using algae, and Evolutionary analysis of human and human society
• Behavior of trace pollutants in water environment
• Food webs, energy flow, and nutrient dynamics in aquatic ecosystems
• Atmospheric Aerosol Dynamics and Environmental Analysis
• Dynamics of adsorption and Reaction on Solid Catalysts

Social System Innovation

• Total Application of Environmental Information for Social Problem
• Ecological design of space and structures
• Sustainable development governance with particular emphasis on climate change policy and politics
• Studies on Economic and Fiscal Policy in Political-Economic Approach
• Historical Studies of Science & Technology
• International comparative study of non-profit organization in Urban Regeneration
• Research on corporate social responsibility, eco management, and environmental accounting
• Environmental Policy History

Mathematical and Numerical Analysis

• Environmental modeling, System simulation, Environmental science on polar region
• Nonequilibrium Dynamics and Numerical Models of Social Systems
• Control theory, Partial differential equations, Agent-Based Simulation
• A Model Analysis on the Effects of Heat Cascading Systems
• Statistical Learning Theory and Its Applications for Medical Science

2009

Number of graduates	39
Number of employed	27
Number of Students Advancing to Master’s Programs	9
Others	3