So Young Sohn

Professor
Yonsei University

Region: Asia-Pacific

Country of residence: South Korea

Contact me for

  • Mentoring
  • Sitting on boards or committees
  • Providing an expert opinion
  • Outreach activities
  • Conference presenting
  • Opportunities to collaborate

Biography

Recent research areas of Industrial Statistics Lab (supervised by So Young Sohn) at Yonsei University, Seoul, Korea encompass patent analytics, technology financing, and spatial big data. Isl’s pioneering work started with the development of technology rating system (K-TRS) which has been being implemented by Korean government agency that is responsible for managing technology credit guarantee fund. ISLers’ effort has contributed to tremendous amount of reduction of risk involved in the guarantee fund and at the same time to identifying innovative firms as tech fund recipients. More recent patent analytics research sponsored by NRF for three consecutive periods (starting from 2013-2024) has similar characteristics to Scisip of NSF. We have proposed quantitative approaches to resolve important issues involved in the pillars consisting of technology financing, patent creation, utilization, protection, infra-structure and searching new areas for intellectual property (IP). In the second phase of the project, we extended the coverage of research scope to social as well as global issues related to IP. Currently, we focus on the research to address new challenges coming from the 4th industrial revolution, by leveraging the cumulated capabilities in quantitative techniques and theoretical backgrounds on innovation. The 4th industrial revolution can be represented by keywords including open culture in innovation and the utilization of general purpose technologies (GPTs) including artificial intelligence. Reflecting the crucial changes in innovation landscape, this research will address the following three research topics: the science and technology in the era of 4th industrial revolution, the open innovation and changes in IP management; and the data science for technological innovation strategy. In addition, Spatial Big Data project sponsored by MOLIT has expanded our perspective to resolve transportation, residence, environmental problems. The combination of the three areas (innovation, finance, spatial big data) resulted in the valuable encounter with regional science for innovation, that can significantly contribute to the sustainable society. Recent accomplishments of the ISL were presented at invited Keynote speech sessions such as CCAI (Chinese Congress on AI) 2019 and the INET (Institute of New Economic Thinking) sponsored Tracking innovation trajectories in the complex economy Conference held in Turin, Italy in 2019.