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Statistical Science of Complex Systems Lab [The Institute of Statistical Mathematics]
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The lab works on statistical analysis of complex systems and the construction of mathematical models.
AboutAbout the lab
Analyzing complex systems with statistics and mathematics.
The Statistical Science of Complex Systems Lab studies statistical analysis of complex systems and the construction of mathematical models.
The research targets differ by faculty member: sustainable resource management, mathematical modeling of neural systems and infectious diseases, and time series analysis of brain activity and plasma turbulence.
The lab is established as a cooperative chair of the Department of Applied Information Sciences, and its faculty are a Visiting Professor and Visiting Associate Professors.
Key terms
- Bayesian statistics
- A statistical method in which inferences expressed as probabilities are updated each time new data are obtained
- Time series analysis
- Analysis that reads out the underlying mechanisms and likely future behavior from a sequence of data that changes over time
- Discrete optimization
- A mathematical method for finding the best choice that satisfies the given conditions among combinations of separate, distinct options
ResearchResearch themes
The lab studies statistical analysis and the construction of mathematical models for complex systems. The targets differ by faculty member: sustainable resource management, analysis of phenomena such as neural systems and infectious diseases, and time series analysis of brain activity and plasma turbulence.
Sustainable resource management for a circular society
Visiting Professor Yoshimoto studies sustainable resource management through fieldwork. Specific research topics include discrete optimization and its economic analysis for consolidating forest land under constraints such as animal movement routes, securing feeding grounds, and the maximum allowable clear-cutting area.
*Illustrative imageMathematical modeling of neural systems and infectious diseases
Visiting Associate Professor Koyama is interested in discovering the structures and patterns behind complex phenomena, and his main methodologies are stochastic modeling and Bayesian statistics. The targets are wide-ranging, including neural systems, metabolic networks, infectious disease models, and social networks.
*Illustrative imageTime series analysis of brain activity and plasma turbulence
Visiting Associate Professor Miwakeichi uses statistical time series analysis to study the structure and prediction of complex and diverse systems. Besides aiming to clarify functional connectivity between neurons and between brain regions, he also studies component decomposition and nonlinear analysis toward predicting the generation of plasma turbulence and its sudden collapse events.
MembersFaculty
- Visiting ProfessorAtsushi Yoshimoto
- Visiting Associate ProfessorFumikazu Miwakeichi
- Visiting Associate ProfessorShinsuke Koyama
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Newly cut logs and clear fell - geograph.org.uk - 3632751” Ann Cook / CC BY-SA 2.0 (cropped)
- Mathematical modeling of neural systems and infectious diseases: “Colorized scanning electron micrograph of a cell (teal) infected with SARS-CoV-2 virus particles (orange), isolated from a patient sample” NIAID / CC BY 2.0 (cropped)
- Time series analysis of brain activity and plasma turbulence: “EAST Tokamak plasma image3” Xiang Gao, Yao Yang, Tao Zhang, Haiqing Liu, Guoqiang Li, Tingfeng Ming, Zixi Liu, Yumin Wang, Long Zeng, Xiang Han et al. / CC BY 3.0 (cropped)
- Related lab (Fluid Systems Informatics Lab): “Turbulent Flow in a Cyclone Separator” SimScale GmbH / CC BY-SA 4.0 (cropped)
- Related lab (Health Informatics Lab): “Blood pressure monitor” Adefanike / CC BY-SA 4.0 (cropped)
- Related lab (Information and Communication Software Lab): “DHL Netherlands local site computer room server racks - IMG 3297” Jemimus / CC BY 2.0 (cropped)
- Related lab (Advanced Applied Data Science Lab): “Transmission electron microscope (2)” Gannu03 / CC BY-SA 4.0 (cropped)
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