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Big Data Engineering Lab
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A lab that researches technologies for handling graphs and language with big data and AI.
AboutAbout the lab
Leading the Big Data Revolution
The Big Data Engineering Lab researches cutting-edge component technologies in areas such as big data, natural language processing, data mining, and artificial intelligence.
Its research themes are wide-ranging, including graph deep learning, graph databases, and large language models.
The lab also aims to create new value by applying its technologies to big data held by companies.
On the lab's website, it is introduced under the name “Onizuka Lab.”
Key terms
- Graph Data
- Data that represents relationships between things as nodes and the links between them. Examples include friendships on social media and road networks
- Large Language Model
- AI that learns the structure, meaning, and knowledge of language from large amounts of language data and can handle natural text
- Graph Database
- A database that manages graph data and makes it searchable. Major companies are also developing them
NewsLab news
Paper by lab members accepted at APWeb-WAIM
Paper by lab members accepted at IEEE ACCESS
Paper by lab members accepted at ACM Computing Survey
Paper by lab members accepted at EMNLP
Paper by lab members accepted at npj Artificial Intelligence
ResearchResearch themes
The lab researches component technologies related to big data and AI in areas such as graphs, language, and databases. It also aims to create new value by applying these technologies to big data held by companies.
*Illustrative imageGraph Deep Learning
The lab works on technologies for processing deep learning on graph data with higher accuracy and speed, and on developing benchmarks to evaluate their performance.
*Illustrative imageGraph Database Management Systems
The lab researches database technologies that efficiently manage large-scale, diverse graph data and enable fast search. It works on indexing, query optimization, and speeding up search with machine learning, and also contributes to international standardization.
Large Language Model Optimization
For large language models that generate and handle text, the lab works on the core technologies of Transformer-based models, adapting models to specific tasks, and ways to improve LLM agents.
Smart Agents
The lab studies “smart agent-based modeling,” which uses foundation models as agents to build models in natural language. It is used to investigate how natural systems work in fields such as economics and behavioral science.
MembersFaculty
The members of the Big Data Engineering Lab are faculty (including Project Assistant Professors and project researchers), visiting faculty, doctoral, master's, and undergraduate students, interns, and staff.As of 2026
- ProfessorMakoto Onizuka
- Associate ProfessorYuya Sasaki
- Associate ProfessorChuan Xiao
- Assistant ProfessorShuyuan Zheng
- Project Assistant ProfessorRonny Hajoon Ko
VoicesStudent voices
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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: “Programming Languages Influence Network Graph freebase yaph” yaph / CC BY-SA 2.0 (cropped)
- Graph Deep Learning: “Deep Learning” Sven Behnke / CC BY-SA 4.0 (cropped)
- Graph Database Management Systems: “Undirected NetworkX Graph” KalebD07 / CC0 (cropped)
- Related lab (Robust Network Engineering Lab): “Raspberry Pi 4 on a network switch” RAIL P (RAIL.PHOTOGRAPHY) / CC0 (cropped)
- Related lab (Advanced High-Performance Computing Infrastructure Systems Lab): “Kraken Supercomputer ( )” Oak Ridge National Laboratory / CC BY 2.0 (cropped)
- Related lab (Nanomaterial Electronics Lab): “Microchip for Carbon Nanotube Field Effect Transistors fabrication” Aidar Kemelbay / CC BY-SA 4.0 (cropped)
- Related lab (Extreme Plasma Engineering Lab): “The moment a high-power laser pulse interacts with a target to produce a plasma is captured at the Vulcan PW facility ( )” Science and Technology Facilities Council / CC BY-SA 2.0 (cropped)
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