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Corinthias P. M. Sianipar: photo

Corinthias P. M. Sianipar

Assistant Professor - Division of Environmental Science and Technology at Kyoto University | Kyoto , Japan

Subjects:
Agriculture, Business, Computer Sciences, Economics, Education, Engineering, Environmental Studies, Geography, Mathematics and Statistics, Public Administration
Spoken languages:
English, Indonesian
Status:
Available for mentoring and open to collaboration.
Support Level:
Short-term mentoring and support
Support Offered:
Writing, Article planning, Dealing with the publishing process, Language polishing/light editing

Work

Subjects:
Education, Engineering, Mathematics and Statistics, Computer Sciences, Economics, Geography, Agriculture, Business, Environmental Studies, Public Administration
Research Keywords:
Systems Thinking, Complex Systems, Systems Modelling, System Dynamics, Agent-Based Modelling, Ecological Economics, Life Cycle Assessment, Green Economy, Sustainability Science, Resilience, Appropriate Technology, Technological Change, Technology Development, Design Engineering, Engineering Design, Circular Economy, Industrial Design, Product Design, Social Engineering, Local Economic Development, Community Development, Community Empowerment, Technology in Society, Information Management, Social Media, Qualitative Methods, Qualitative Research
Collaboration interests:
Collaborative writing. Research coaching. Peer reviewing.
Biography:
Dr. Corinthias P.M. SIANIPAR specializes in complex systems analysis (Systems Engineering, System Dynamics, Agent-Based Modeling, Discrete-Event Simulation, Stochastic Optimizations), technological appropriateness (Socio-Technical Systems, Appropriate Technology), and life-cycle assessment (LCA/Social LCA, Circular Economy) within the science-to-policy-to-action framework. A versatile scholar trained in both engineering and social science educations, he has more than ten years of experience in delivering systemic and systematic socio-technical solutions for different development contexts. He applies a combination of computational modeling and qualitative analysis to pursue an "adequate fit of innovation" for communities having technical inadequacy, lacking economic resources, suffering environmental constraints, and experiencing social confrontations.

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