Jae-Min Song
Seoul National University · 工学
研究室紹介
Professor Jae-Min Song's research spans sustainable development, urban sustainability, and data-driven decision making, with a strong focus on integrating machine learning and systems thinking to address complex societal challenges. His work applies advanced analytical methods—such as semantic network analysis, Word2Vec, and LSTM-based models—to understand interlinkages among Sustainable Development Goals (SDGs), assess urban sustainability in rapidly developing contexts like South Korea, and improve financial and media consumption forecasting. He bridges policy, technology, and data science to generate actionable insights for national and global sustainability goals. His research also extends to behavioral analytics in digital media, particularly mobile TV usage and video-on-demand adoption.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Abstract Understanding sustainable development goal (SDG) targets and their interlinkages is crucial for achieving national and local SDGs since policies must be designed and implemented at the target level rather than at the macro goal level. However, due to their extensive nature, it remains challenging to fully determine their interlinkages. This study aims to identify the interlinkages between the SDG targets, employing a semantic network analysis with text‐mining and Word2Vec machine‐learni
The ROK has experienced unprecedented rapid urbanization since the Korean War. Cities have been critical engines for economic development as hubs of innovation and efficiency. However, they have also faced diverse urban challenges during the process of swift urbanization. Thus, the urbanization process needs to be assessed through the lens of sustainability, based on an integrated approach that evaluates the performance of the ROK and provides implications for developing countries. Against this
Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2010.