Ichiro Sakata

The University of Tokyo

Papers

5

Total Citations

166

H-Index

3

About

Ichiro Sakata is a prominent researcher whose work sits at the intersection of technology analysis, innovation studies, and knowledge discovery. His scholarship focuses on understanding how emerging technologies evolve, converge, and connect to broader societal challenges — areas that have become increasingly vital in an era of rapid technological transformation. Sakata's most influential contribution lies in his development of Literature Based Discovery (LBD) approaches to identify meaningful linkages between technology and pressing social issues, such as aging societies and sustainability. His 2013 paper on this method has garnered 83 citations, demonstrating its significant uptake within the research community. Complementing this, his 2018 work on technology convergence in robotics — attracting 73 citations — has proven foundational for scholars seeking to map how disciplines like mechanical engineering, control systems, electronics, and software increasingly merge to drive innovation. Through a sustained body of work on robotics research, including studies detecting emerging complex technological fields and tracing advancement trajectories, Sakata has established himself as a key figure in science and technology mapping. His research provides policymakers and industry leaders with powerful analytical tools to anticipate technological trends and strategically align innovation efforts with societal needs.

Research Focus

Key Achievements

3
H-Index
5
Papers
166
Total Citations
33
Avg Citations/Paper
🏆 Most Cited Paper
Finding linkage between technology and social issue: A Literature Based Discovery approach
83 citations · 2013
📈 Most Prolific Year: 2013 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: The University of Tokyo

Top Papers

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  5. 5
    Finding linkage between technology and social issues: A literature based discovery approach
    3 citations · 2012

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago