Felipe Kenji Nakano
Felipe Kenji Nakano is a senior researcher in itec, imec research group at KU Leuven, funded by FWO. He is mainly working on structured output prediction tasks with imperfect data applied to (bio) medical problems. His main research areas of interest are (hierarchical) multi-label classification, multi-target regression, semi-supervised learning, active learning, positive-unlabeled learning, weak-label learning. Apart from his research work at itec, Felipe is also involved in the advanced master of Artificial Intelligence in Business and Industry at the KU Leuven campus Kulak in Kortrijk.
Domain/sector
- Computer Science & IT
- Healthcare, Biomedical Sciences & Sports
Personal info
courses
Artificial Intelligence in Business and Industry
postgraduate certificate - Kortrijk - KU Leuven, PUC KU Leuven Continue, VAIA