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[LIFE SCIENCE] Tanaka Team

Development of AI Technologies for Biomedical Informatics and Its Applications

Team Head

Toshihisa Tanaka

Affiliation Institute of Engineering
Division / Department Division of Advanced Electrical and Electronics Engineering
Position Professor
URL http://tanaka.sip.tuat.ac.jp/

Foreign Researcher(s)

Andrzej Cichocki

Affiliation Skolkovo Institute of Science and Technology (Russia)
Division / Department Center for Computational and Data-Intensive Science and Engineering
Position Professor
URL http://faculty.skoltech.ru/people/andrzejcichocki

Antonio Ortega

Affiliation University of South California (U.S.A.)
Division / Department Department of Electrical Engineering
Position Professor
URL http://biron.usc.edu/wiki/index.php/Antonio_Ortega

Anh-Huy Phan 

Affiliation Skolkovo Institute of Science and Technology (Russia)
Division / Department Center for Computational and Data-Intensive Science and Engineering
Position Assistant Professor
URL https://faculty.skoltech.ru/people/anhhuyphan

Fabien Lotte

Affiliation Institut National de Recherche en Informatique et en Automatique (France)
Division / Department
Position Research Scientist
URL https://sites.google.com/site/fabienlotte/Home

Members

Toshiyuki Kondo (Institute of Engineering / Professor), Akinobu Shimizu (Institute of Engineering / Professor), Yuichi Tanaka (Institute of Engineering / Associate Professor), Katsuhide Fujita (Institute of Engineering / Associate Professor), Ken Takiyama ((Institute of Engineering / Associate Professor), Islam MD Rabiul (Institute of Global Innovation / Assistant Professor)

Overview

Recent advances of AI have been mainly developed based on machine learning technologies that extract features and knowledge from a large amount of data. However, in many cases, it is difficult to collect big data (aka small data), so current AI technologies have a limitation for discovering knowledge from data. In particular, biosignals and bioinformation, such as electroencephalogram (EEG) and functional MRI, has difficulty in collecting data.
This research team attacks the limitation of the small data problem by establishing signal processing techniques that can exploit biosignals to develop “biosignal AI.” Moreover, based on these technologies, we aim to bring a big progress on neurorehabilitation and human—computer interfaces. TUAT has active researchers in this field, so we promote an international collaboration to achieve this goal.

Approaches

We aim to establish novel technologies based on recently developed advanced signal processing and AI technologies. By applying “signal processing + AI,” we try to efficiently extract useful information from biosignals and to develop sophisticated neurorehabilitation techniques, medical diagnosis-aid, and brain-machine interfaces.

Plan

This team leads AI research in TUAT. To this end, the team has two sub-groups, including a group for biosignal processing and another group for bio-applications. We also collaborate with RIKEN AIP (advanced intelligence project) center. We invite two adjunct distinguished professors, Dr. A. Cichoski and Dr, A. Ortega. Dr. Cichocki is a pioneer of blind source separation and brain-computer interfaces. Dr. Ortega is a pioneer of wavelets and graph signal processing.

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