SISA 2013

Keynote Speech

Era of Big Data Processing: A New Approach via Tensor Networks and Tensor Factorizations


Invited Speaker:

Dr. Andrzej CICHOCKI
RIKEN Brain Science Institute, Japan


Multidimensional data is becoming ubiquitous across the sciences and engineering because they are increasingly being gathered by information-sensing devices and remote sensing. Big data (such as multimedia data (speech, video, and medical/biological data) analysis requires novel technologies to efficiently process large quantities of data within tolerable elapsed times. Such a new emerging technology for multidimensional big data is a multiway analysis via tensor networks and tensor decompositions. Modern applications such as computational neuroscience, bioinformatics and pattern/image recognition generate massive amounts of data with multiple aspects and high dimensionality. Tensors (i.e., multi-way arrays) and tensor networks provide a natural representation for such massive multidimensional data. Dynamic tensor analysis allows us to discover meaningful hidden structures of complex data and perform generalizations by capturing multi-linear and multi-aspect relationships. The challenge is how to analyze intractably large-scale, tensor-structured data sets. Data explosion creates deep research challenges that require new scalable, tensor decomposition algorithms. One of the challenge in computational and system neuroscience is to understand the relationship between perception, cognition, emotions and behaviors. We will present emerging models and associated algorithms for large-scale tensor decompositions and their applications to Brain Machine Interface (BMI), EEG Hyper-scanning, multilinear blind source separation and early prediction (diagnosis) of Alzheimer disease. Our algorithms allow to process and decompose much larger tensors compared to previous methods and are promising tools for feature extraction, classification, cluster analysis, data fusion and integration, pattern recognition, anomaly detection, predictive modeling, regression, time series analysis and 3D visualization.


Andrzej CICHOCKI received the MSc (with honors), PhD and Dr Sc (Habilitation) degrees, all in electrical engineering, from Warsaw University of Technology (Poland). Since 1976, he has been with the Institute of Theory of Electrical Engineering, Measurement and Information Systems, Faculty of Electrical Engineering at the Warsaw University of Technology, where he became a full Professor in 1995. He spent several years at University Erlangen-Nuerenberg (Germany) as an Alexander-von-Humboldt Research Fellow and Guest Professor. In 1995-1997 he was a team leader of the Laboratory for Artificial Brain Systems, at Frontier Research Program RIKEN (Japan), in the Brain Information Processing Group. He is currently a Senior Team Leader and Head of the laboratory for Advanced Brain Signal Processing, at RIKEN Brain Science Institute (Japan). He is (co)author of more than 300 technical journal papers and 4 monographs (books) in English (two of them translated to Chinese): Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis, John Wiley-2009; Adaptive Blind Signal and Image Processing (co-authored with Professor Shun-ichi Amari, Wiley, 2003), MOS Switched-Capacitor and Continuous-Time Integrated Circuits and Systems (co-authored with Professor Rolf Unbehauen; Springer-Verlag, 1989) and Neural Networks for Optimizations and Signal Processing (Wiley-1994). He has served as an Associated Editor of IEEE Transactions on Neural Networks, IEEE Transactions on Signals Processing and as a founding Editor in Chief for Journal Computational Intelligence and Neuroscience. Currently, his research focus on multiway analysis, tensor decompositions, blind sources separation, brain machine interface, EEG hyper-scanning, human to robot interaction and their practical applications. His publications currently report over 19,000 citations (his h-index is 59).

Invited Speech

Novel biosensor approaches for biomedical applications


Invited Speaker:

Dept. of Biomedical Devices and Instrumentation,
Institute of Biomaterials and Bioengineering,
Tokyo Medical and Dental University, Japan


Rapid increasing of diabetes mellitus is now global problem and development of a safe and non-invasive and continuous method of blood sugar monitoring is strongly requested. We paid attention to the relationship between the tear glucose level and the blood sugar level. In this lecture, a soft contact lens type glucose sensor using biocompatible polymers will be introduced. The biosensor was designed for continuous glucose monitoring in tear fluids on eye site. In order to achieve flexibility and biocompatibility, the biosensor utilizes some functional polymers. Owing to the flexible laminar structure of the polymers, the sensor fits the rounded shape of human body and has good biocompatibility. The sensor measures the glucose concentration as a current change induced by enzyme reaction at the GOD immobilized polymer layer. In the MEMS fabrication process, film electrodes were formed on polymer substrate using sputtering method. The sensor also showed high flexibility and was soft and comfort to the touch. The sensor showed linearity in glucose level of 0.05 - 3.00 mmol/l with a correlation coefficient of 0.998. The calibration range includes the reported concentration of tear glucose in normal human subject. The sensor was attached on the rabbit eye as mentioned before and tear glucose level of the rabbit eye was monitored continuously. In this lecture, I will also show other unique bio-devices (i.e. biochemical gas-sensors, spatiotemporal smell-imaging, artificial actuators and organs with chemo-mechanical conversion system) for the medical and healthcare applications in the near future.


Kohji Mitsubayashi received the degree of B.E. (1983) and M.E. (1985) in Mechanical Engineering from Toyohashi University of Technology, and the Ph.D. degree in Interdisciplinary Course on Advanced Science and Technology from the University of Tokyo (1994). He worked as a company researcher at DENSO Corporation (1985-1998). He was an associate Professor in the Department of Electrical Engineering (1998-2001) and Information sciences (2001-2003) at Tokai University. Since 2003, he has been a Professor in the Department of Biomedical Devices and Instrumentation at Tokyo Medical and Dental University. His research interests includes wearable biosensors with Soft-MEMS techniques for non-invasive biochemical-monitoring, biochemical gas sensors (Bio-sniffer) and gas visualization system for human odor and halitosis analysis, novel artificial organs (hands, pancreas) with “Organic Engine” converting from chemical to mechanical energy, etc.