Mathematical Informatics
Research Staff

Professor
Kazushi IKEDA 
Affiliate Professor
Junichiro YOSHIMOTO 
Affiliate Professor
Toshitaka YAMAKAWA 
Associate Professor
Takatomi KUBO 
Affiliate Associate Professor
Tomoya TAMEI 
Assistant Professor
Makoto FUKUSHIMA 
Assistant Professor
Chie HIEIDA 
Assistant Professor
Renzo Roel Perez TAN
Research Areas
Fig.1 Mathematical models in computation
Fig.2 Mathematical models in science
Fig.3 Mathematical models in engineering
We study mathematical models for life sciences, from cell biology and neuroscience to medical science and social interaction. Our interdisciplinary research covers computation (machine learning), science (mathematical biology) and engineering (signal processing).
Machine learning
 Statistical learning theory
 Statistical signal processing based on Bayes theory
 Neural network theory
 Information geometry and information theory
 Factor analysis and sparse models
 Reinforcement learning theory and applications
Mathematical biology
 Math models for cell biology
 Modeling and medical decision support for neuropsychiatric discorders
 Neural mechanism of empathy
 Behavior analysis using smart sensors
 Cognitive interaction design and social interaction
Signal processing
 Advanced driver assistance systems
 Adaptive signal processing theory and application
 Noninvasive humanmachine interfaces
 Anomaly diagnosis by bigdata analysis
 Deep learning methods and application
Key Features
Mathematical informatics is interdisciplinary; faculty and students in our lab have a variety of backgrounds, such as mathematical engineering, electric and electronic engineering, mechanoinformatics, statistical science, physics, psychology, social science and medical science. We welcome students from any background since "mathematical models are everywhere", as long as they are interested in mathematical models.