LAB LOGA page on LabLog, a review site (not the lab's official page)
Aoshima Lab
Machine-translated · View original
The lab develops theory and methods for the statistical analysis of high-dimensional data.
AboutAbout the lab
Reading high-dimensional data through mathematics
Aoshima Lab studies theory and methodology for the statistical analysis of high-dimension, low-sample-size (HDLSS) data, in which the dimension is far larger than the sample size.
Genomic data, for example, involve tens of thousands to millions of genes but only a few dozen subjects.
It has been mathematically proven that conventional statistics cannot guarantee accuracy for such data and can sometimes give wrong answers.
With the research stance of accurately understanding the mathematical foundations behind statistics, the lab is pioneering new statistical theory and methodology.
Key terms
- High-dimension, low-sample-size (HDLSS) data
- Data whose dimension is far larger than its sample size. Genomic data are an example
- Genomic data
- An example of HDLSS data. The dimension corresponds to the number of genes, and the sample size to the number of subjects
- HDLSS asymptotic theory
- A unified approach for giving statistical accuracy guarantees to the methodologies the lab has developed
NewsLab news
A doctoral student received the Excellent Presentation Award at the poster session of the Spring Meeting of the Japan Statistical Society
A master's student received the Student Excellent Presentation Award at the poster session of the Spring Meeting of the Japan Statistical Society
A doctoral student received the Best Poster Presentation Award at the Interdisciplinary and Cross-Industry Research Exchange Meeting 2025
A master's student received the Dean's Award of the Graduate School of Pure and Applied Sciences at the University of Tsukuba and the Meikeikai Award
A master's student received the Excellent Presentation Award at the FY2024 Japanese Joint Statistical Meeting
ResearchResearch themes
One characteristic of data in modern science is that the dimension is far larger than the sample size. Going beyond the framework of conventional statistics, the lab builds theory and methodology for high-dimensional data analysis based on new ways of thinking.
View More ↗
MembersFaculty
Members of Aoshima Lab include faculty, researchers, and students in the doctoral program, the master's program, and the undergraduate school.As of 2025
- ProfessorMakoto Aoshima
- ProfessorKazuyoshi Yata
VoicesStudent voices
Ratings and reviews reflect the experiences of individual current or former students, not the lab's official views. Whether a lab has reviews, or how many, says nothing about the lab itself.
Students who take part in an interview may receive a thank-you gift worth ¥1,000, regardless of what they say.
Student ratings (0 students)
--
--
--
--
--
--
Student voices answer questions like these
- What's great about this lab?
- What did you learn after joining?
- What's the vibe, and what is the professor like?
- Who is this lab for?
- Where do graduates go?
Your experience can help younger students choose their lab. Your name won't be shown.
Write a lab reviewAnonymous · Your draft is saved if you stopRelatedLabs similar to Aoshima Lab
Ohyauchi LabSchool of Science and Engineering, College of MathematicsBayesian approaches to statistical inference theory for non-…
Yata LabSchool of Science and Engineering, College of MathematicsMultivariate analysis, sequential analysis, analysis of high…
Takeuchi LabSchool of Science and Engineering, College of MathematicsMathematical logic, model theory, especially stability theor…
Terui LabSchool of Science and Engineering, College of MathematicsComputer algebra, in particular the theory and applications …The information on this page is compiled by the LabLog team from the lab's public information and interviews. For corrections or removal requests, please contact LabLog, not the lab.
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: “Mechanical-calculator-Brunsviga-15-01” CEphoto, Uwe Aranas / CC BY-SA 3.0 (cropped)
- Theory and Methodology for High-Dimensional Data Analysis: “Microarray (NIH BioArt 736)” Courtesy of NIAID Ryan Kissinger / Public domain (cropped)
- Related lab (大谷内 奈穂 研究室): “Jeffreys prior probability for the beta distribution - J. Rodal” Dr. J. Rodal / CC BY-SA 3.0 (cropped)
- Related lab (矢田 和善 研究室): “Climate data analysis using tSNE method” Orlovma / CC BY 4.0 (cropped)
- Related lab (竹内 耕太 研究室): “Classroom blackboard at Cornell University, Ithaca, NY 25” LBM1948 / CC BY-SA 4.0 (cropped)
- Related lab (照井 章 研究室): “Kreis Maxima” Birgit 18 / CC BY-SA 4.0 (cropped)
About LabLog
LabLog is a lab review app for students only. Student members at each university interview students in labs and publish what they say. Student voices can only be read by students who sign up with a university email address. Operated by bestiee Inc.
Learn more about LabLog ↗Search engines and AI may reference the basic lab info and rating summaries on this page and the description of LabLog. Student voices are for student members only. Automated collection by programs (scraping, or input to or training of AI) is prohibited under Article 8 of the Terms of Service. If you need data for research or analysis, please contact us.