Interdisciplinary Research using Large-scale Information Infrastructure
Etsuya Shibayama
Information Technology Center
Professor
We promote joint research such as for countermeasures against global warming and natural disasters, i.e. earthquakes and tsunamis, and advanced medical diagnosis support by using the massive research resources of the Information Technology Center, the University of Tokyo.
We contribute to a wide range of research fields through interdisciplinary joint research activities by employing the cutting-edge computational resources for simulation and data analysis as well as tapping into a professional network of researchers of various fields in both academia and industry.
With the development of high-performance computing and artificial intelligence (AI) technologies, we are working to solve various problems. Our activities include (1) joint research with researchers in industry on global warming countermeasures by evaluating long-term stability of geologic carbon dioxide sequestration for more than 1,000 years through efficient large-scale simulation; (2) joint research on improving the performance of medical image analysis using machine learning for early detection of various diseases; and (3) joint research on realistic simulation of big earthquakes for greater preparedness against disaster.
We contribute to a wide range of research fields through interdisciplinary joint research activities by employing the cutting-edge computational resources for simulation and data analysis as well as tapping into a professional network of researchers of various fields in both academia and industry.
With the development of high-performance computing and artificial intelligence (AI) technologies, we are working to solve various problems. Our activities include (1) joint research with researchers in industry on global warming countermeasures by evaluating long-term stability of geologic carbon dioxide sequestration for more than 1,000 years through efficient large-scale simulation; (2) joint research on improving the performance of medical image analysis using machine learning for early detection of various diseases; and (3) joint research on realistic simulation of big earthquakes for greater preparedness against disaster.
Hajime Yamamoto, Taisei Corporation
Related links
Related publications
- H. Yamamoto, K. Nakajima, K. Zhang, and S. Nanai, “Performance of Parallel Simulators on Peta-scale Platforms for Coupled Multi-physics Modelling of CO2 Geologic Sequestration”, Energy Procedia, 63, pp. 3795-3804, (2014).
- Nomura Y., Higaki T., Fujita M., Miki, S., Awaya Y., Nakanishi T., Yoshikawa T., Hayashi N., Awai K., "Effects of Iterative Reconstruction Algorithms on Computer-assisted Detection (CAD) Software for Lung Nodules in Ultra-low-dose CT for Lung Cancer Screening", Academic Radiology, 24(2), 124-130, (2017).
- R. Ando, “Fast Domain Partitioning Method for dynamic boundary integral equations applicable to non-planar faults dipping in 3-D elastic half-space”, Geophys. J. Int. 207, 833-847, (2016).
- Nakajima, K., Satoh, M., Furumura, T., Okuda, H., Iwashita, T., Sakaguchi, H., Katagiri, T., Matsumoto, M., Ohshima, M., Jitsumoto, H., Arakawa, T., Mori, F., Kitayama, T., Ida, A., and Matsuo, M.Y., ppOpen-HPC: Open Source Infrastructure for Development and Execution of Large-Scale Scientific Applications on Post-Peta-Scale Supercomputers with Automatic Tuning (AT), Optimization in the Real World, Mathematics for Industry 13, 15-35, Springer, (2015).
- Nomura Y., Higaki T., Fujita M., Miki, S., Awaya Y., Nakanishi T., Yoshikawa T., Hayashi N., Awai K., "Effects of Iterative Reconstruction Algorithms on Computer-assisted Detection (CAD) Software for Lung Nodules in Ultra-low-dose CT for Lung Cancer Screening", Academic Radiology, 24(2), 124-130, (2017).
- R. Ando, “Fast Domain Partitioning Method for dynamic boundary integral equations applicable to non-planar faults dipping in 3-D elastic half-space”, Geophys. J. Int. 207, 833-847, (2016).
- Nakajima, K., Satoh, M., Furumura, T., Okuda, H., Iwashita, T., Sakaguchi, H., Katagiri, T., Matsumoto, M., Ohshima, M., Jitsumoto, H., Arakawa, T., Mori, F., Kitayama, T., Ida, A., and Matsuo, M.Y., ppOpen-HPC: Open Source Infrastructure for Development and Execution of Large-Scale Scientific Applications on Post-Peta-Scale Supercomputers with Automatic Tuning (AT), Optimization in the Real World, Mathematics for Industry 13, 15-35, Springer, (2015).
