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Ueno Lab
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The lab studies Bayesian networks and e-testing.
AboutAbout the lab
Repeating theory and practice to pursue research that can truly contribute to society
The Ueno Lab studies artificial intelligence, statistics, Bayesian theory, machine learning, natural language processing, and more.
Besides theoretical research on Bayesian networks and software development and applied research, the lab also develops e-testing and e-learning systems.
The lab aims for "research that can truly contribute to society" by repeatedly cycling between theoretical research and practice.
Key terms
- Bayesian network
- A model that represents probabilistic relationships as a network and can perform inference by combining the user's prior knowledge
- E-testing
- The practice of administering examinations, such as national examinations, on computer-based systems
- Topic model
- A probabilistic model for automatically learning the content (topics) of text
NewsLab news
View More ↗ResearchResearch themes
The lab studies artificial intelligence, statistics, Bayesian theory, machine learning, natural language processing, e-learning, e-testing, and more. It aims for "research that can truly contribute to society" by repeatedly cycling between theoretical research and practice.
*Illustrative imageBayesian Networks
The lab studies structure learning, probabilistic inference, and learning as classifiers for Bayesian networks, which can perform inference by combining prior knowledge. It has achieved exact structure learning with more than 3,000 variables and has also developed its own software, "Bayesian Discovery."
*Illustrative imageE-Learning That Supports Learning
The lab has continued this research since before the term "e-learning" existed. It aims for systems that induce natural learning rather than teach, and that manage learning. A representative example is the learning management system "Samurai."
*Illustrative imageBayesian Natural Language Processing
The lab developed a report recommendation system that automatically learns the content (topics) of text, using latent semantic analysis (LDA) with topic models. It is also developing technology for automatically composing text.
*Illustrative imageE-Testing Systems
E-testing is advancing rapidly in many national examinations, including the IPA Information Technology Engineers Examination, Japan's largest national examination. The lab has been entrusted with its planning and design, and aims to build the world's best e-testing system.
MembersFaculty
The Ueno Lab's members consist of faculty and students in the doctoral program, the master's program, and the undergraduate level.As of 2026
- ProfessorMaomi Ueno
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: “Bayesian network” Sachs K, Gifford D, Jaakkola T, Sorger P, Lauffenburger DA. / CC BY-SA 4.0 (cropped)
- Bayesian Networks: “Bayesian network gene” Lorenahoxhallari / CC BY-SA 4.0 (cropped)
- E-Learning That Supports Learning: “E-learningE-E-Learning Computer” LeanForward lf / CC BY-SA 2.0 (cropped)
- Bayesian Natural Language Processing: “Elliot Bay Book Company interior” Lucytestwuide / CC BY 4.0 (cropped)
- E-Testing Systems: “Large group of apprentices seated for their first exam at the Hutt Railway Workshops in 1930, situated in the staff social hall at the workshops ATLIB 311637” Godber, Albert Percy / Public domain (cropped)
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- Related lab (原 聡 研究室): “Client Project Hashcat Testing With an AMD Epyc Supermicro Nvidia GPU Server Using Proxmox (Lawrence Systems) 07” Lawrence Systems / CC BY 3.0 (cropped)
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