معرفی
Manabu Kobayashi is a Professor at the Center for Data Science of Waseda University, with previous faculty roles at Shonan Institute of Technology (1998-2014). His research spans data mining, machine learning, and information theory, with a focus on applications in document classification, ECOC frameworks, and latent structural models.
- Current Affiliation: Waseda University (2018-present)
- Previous: Shonan Institute of Technology (2002-2014)
Research Interests: Specializes in distance metric learning, latent class modeling, and fault diagnosis systems using probabilistic frameworks. Key areas include:
- ECOC (Error-Correcting Output Codes) optimization
- Collaborative filtering for recommendation systems
- Reconfigurable logic circuits using DG-CNTFETs
- Privacy-preserving distributed linear regression
Scientific Awards:
- PC Conference Best Paper Award (2025)
- World CIST'18 Best Paper Award
- IEICE Achievement Award (2017)
- 74th Information Processing Society of Japan Conference Excellence Award (2012)
Article Trends: Recent work focuses on latent structure analysis for relational data (2025), ECOC performance with noisy classifiers (2023), and flipped classroom effectiveness through log-based grouping (2022-2025). Earlier contributions include reconfigurable logic circuits (2013-2014) and probabilistic fault diagnosis (2011-2012).