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Data Generation Engineering Lab
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The lab simulates a virtual real-world society that includes human beings.
AboutAbout the lab
From a “future by chance” to a “future we dream of”
The Data Generation Engineering Lab develops real-scale social simulation (RSSS) technology, which reproduces a virtual real-world society that includes human elements.
On a digital twin of real society built in cyberspace, the lab simulates individual decision-making, such as movement and purchasing behavior.
On the lab's website, under the name “RSSS Laboratory,” it is introduced as working on developing the elemental technologies needed to safely realize real-world-scale simulation.
The lab advances research on data generation in the fields of social simulation and drug discovery.
Key terms
- Real-scale social simulation
- Technology that reproduces a virtual real-world society including human elements and simulates individual decision-making. Abbreviated RSSS
- Digital twin
- A virtual copy of real society or real objects, recreated in cyberspace
- Synthetic population data
- Data in which the attributes of individuals and households are artificially generated from statistics such as the national census
NewsLab news
View More ↗ResearchResearch themes
The lab works on developing the elemental technologies needed to safely realize real-world-scale simulation. On a digital twin of real society built in cyberspace, it simulates individual decision-making, such as movement and purchasing behavior.
*Illustrative imageReal-scale social simulation
The lab develops simulation technology that reproduces a virtual real-world society including human elements. Using a digital twin in cyberspace, it handles individual decision-making such as movement and purchasing behavior.
*Illustrative imageAssigning workplace locations to synthetic population data
The lab studies methods for assigning workplace locations, meaning the municipality or area where each person works, to the employed people in synthetic population data. It improved consistency with statistics such as the national census and showed that daytime population can be simulated at a nationwide scale.
MembersFaculty
The members of the Data Generation Engineering Lab consist of faculty, visiting researchers, master's and undergraduate students, and secretaries.As of 2026
- ProfessorTadahiko Murata
- Associate ProfessorChen Li
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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: “দোল উৎসব” Latentlife.archive / CC BY-SA 4.0 (cropped)
- Real-scale social simulation: “Agent-based-simulation-of-design-team” Marc Ramsey and Paul Collopy / CC BY-SA 3.0 (cropped)
- Assigning workplace locations to synthetic population data: “Map Urban development - Milano 1992 - Incoming commuting with private transport - Touring Club Italiano CART-TEM-054 (cropped)” TCI Cartographic Office / CC BY-SA 4.0 (cropped)
- Related lab (Advanced High-Performance Computing Infrastructure Systems Lab): “CSCS Supercomputer Alps 2” CS / CC BY-SA 3.0 (cropped)
- Related lab (Big Data Engineering Lab): “NOIRLab HQ Server Racks (6V6A0404-CC)” NOIRLab/NSF/AURA/T. Slovinský / CC BY 4.0 (cropped)
- Related lab (Intelligent Information Systems Lab): “Wikimedia Foundation Servers-8055 03” Victorgrigas / CC BY-SA 3.0 (cropped)
- Related lab (Multimedia Agent Lab): “EZ-Robot Humanoid software” Bobjgalindo / CC BY 4.0 (cropped)
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