Hiroshi Okamoto

Time-resolved optical measurements and non-perturbative theoretical analyses of photo-and electric-field-responses in correlated electron systems

Research Director

Hiroshi Okamoto

Collaborator

Kaoru Iwano	Lecturer Institute of Materials Structure Science High Energy Accelerator Research Organization
Akira Takahashi	Professor Graduate School of Engineering Nagoya Institute of Technology
Takami Tohyama	Professor Faculty of Science Tokyo University of Science

Outline

Correlated electron systems excited with an intense and ultrafast light pulse are expected to show non-equilibrium electronic-structure changes and ultrafast electronic phase transitions, which cannot be analyzed with conventional perturbation theories. In this research project, we perform integrally “the experimental study of non-perturbative electronic responses with time-resolved optical spectroscopy” and “the formulation of analysis methods of transient optical spectra by the combination of exact calculation with big data analysis and data assimilation.” By applying developed analysis methods to spectroscopic data, we aim to unravel physical mechanisms of photo- and electric-field-responses in correlated electron systems.

Tamiki Komatsuzaki　

Development of Accelerated Measurement Techonology for Cell Diagnosis by bridging Single-Cell Raman Imaging and Information Science

Research Director

Tamiki Komatsuzaki　

Collaborator

Yoshinori Harada	Associate Professor Graduate School for Medical Sciences Kyoto Prefectural University of Medicine
Katsumasa Fujita	Professor Graduate School of Engineering Osaka University

Outline

We develop a novel technology for molecular Raman measurements that constantly feeds optimal conditions back to the measuring equipment. Using the techniques of information science and statistical mathematics to analyze spectral imaging data of cells and living tissues, the technology aids in speedy and highly accurate diagnoses. We introduce our technology in the diagnosis of cancer, which currently relies on morphometric information of cells and tissues. We aim for the creation of a molecular measurement technique in the fields of life science, medicine, and drug-discovery by enabling early diagnosis of diseases that are difficult to diagnose.

Kaoru SATO

Study of atmospheric hierarchical structure by fusion of observation data from a global radar network and high-resolution general circulation models

Research Director

Kaoru SATO

Collaborator

Koji Nishimura	Associate Professor The Research Institute for Sustainable Humanosphere (RISH) Kyoto University
Daisuke Matsuoka	Researcher Research Institute for Value-Added-Information Generation Japan Agency for Marine-Earth Science and Technology
Shingo Watanabe	Vice Director Research Institute for Global Change Japan Agency for Marine-Earth Science and Technology

Outline

An assimilation technique will be developed for high-resolution general circulation models using the low-resolution and global observation data from satellites in combination with the high-resolution and sparse observation data from international collaboration with a global MST-radar network including the PANSY radar, the first MST radar in the Antarctic that the PI’s group has recently constructed at Syowa Station. In addition, using the assimilation technique, a high-resolution grid data of the global atmosphere extending from the surface to the ～100 km altitude will be created and the physics of the hierarchical structure embedded in the atmosphere will be elucidated.

Yasukazu Murakami

Advanced electron microscopy with the aid of artificial intelligence and image processing

Research Director

Yasukazu Murakami

Collaborator

Hiroyuki Shinada	Technology Advisor Research & Development Group Hitachi, Ltd.
Yoshihiro Midoh	Assistant Professor Graduate School of Information Science and Technology Osaka University

Outline

The aim of this research project is to improve the precision of electron holography, which reveals local electromagnetic field of materials, with the aid of advanced information science including image processing assisted by artificial intelligence (AI), retrieval of the phase information from obscured electron holograms, and other such techniques. An ultimate goal is to achieve a precision that allows for examinations of weak electric potential due to single electron. The results will provide a key, for example, for deeper understanding of the mechanism underlying catalytic reactions in nanoparticles, and accordingly contribute to social issues related with energy generation etc.

Genki Yoshikawa

Development of a standard multi-dimensional mega-library of odors and classification accuracy assessment using interpretable predictive models

Research Director

Genki Yoshikawa

Collaborator

Katsuhiko Ariga	MANA Principal Investigator International Center for Materials Nanoarchitectonics National Institute for Materials Science
Junko Watanabe	Senior Expert Data Science Research Laboratories NEC Corporation

Outline

The practical olfactory sensors are expected to create new industries. In this study, a standard multi-dimensional mega-library of odors will be constructed by means of the newly developed highly sensitive sensor “MSS” functionalized by various advanced materials. The integration of the cutting-edge data analysis technique called “Factorized Asymptotic Bayesian Inference” will provide quantitative guidelines for the long-standing issue on olfactory sensors: “How much classification accuracy can be achieved on what conditions?”

Takashi Washio

Exploration of Novel Measurement and Analysis Approaches by Deep Synthesis and Investigation of Machine Learning and Advanced Measurement Technologies

Research Director

Takashi Washio

Collaborator

Masateru Taniguchi

Professor The Institute of Scientific and Industrial Research Osaka University

Outline

This study explores new measurement and analysis approaches overcoming the current limits on the observing objects and the accuracies by deep synthesis and invastigation of machine learning and advanced measurement technologies. We particularly develop novel approaches of feature extraction from data, small sample based estimation using prior knowledge, synthetic estimation from multiple information sources and machine learning reflecting measurement process for the advanced measurements. We apply these novel approaches to a highly efficient and low cost nano-gap, nano-pore based DNA sequencing system as a test bed.