LAB LOGA page on LabLog, a review site (not the lab's official page)
Kabashima Lab
Machine-translated · View original
The lab applies the ideas of statistical mechanics to solve problems in information and communication and in machine learning.
AboutAbout the lab
The mathematics and physics hidden in countless things.
The Kabashima Lab studies a wide range of problems in information science based on the ideas of statistical mechanics.
Statistical mechanics is a field that seeks to explain the collective behavior that emerges when a large number of small elements, such as atoms and molecules, come together.
It has become clear that theories developed through phenomena such as water turning into ice and iron becoming a magnet can also be used for compressing files and recovering corrupted data.
Focusing on error-correcting codes, compressed sensing, and machine learning, the lab is opening up a new area between theoretical physics and information science.
Key terms
- Statistical mechanics
- A field of physics that explains the characteristic collective behavior that emerges when a large number of small elements come together
- Error-correcting codes
- A mechanism that adds information in advance so that data can be restored even if it is corrupted during communication or storage
- Compressed sensing
- A signal processing method for recovering the original signal or image from a small amount of observed data
ResearchResearch themes
The lab tackles a variety of problems in information science, including information and communication and machine learning, based on statistical mechanics, a way of thinking from physics. It uses the view that considering the limit in which the problem size becomes infinitely large reveals properties and solution methods that cannot be seen by solving the problem as it stands.
*Illustrative imageStatistical Mechanics of Error-Correcting Codes
The lab treats error-correcting codes, which restore corrupted data, as models of a hypothetical magnetic material. By applying the concept of phase transitions and the analytical methods developed in the statistical mechanics of disordered systems, it quantitatively examines the performance of codes.
*Illustrative imageDetection of Mixed Communication Signals
The lab formulated the problem of separating the signals of multiple users in CDMA, a scheme used in mobile phones and wireless LANs, as Bayesian inference. It then develops approximate algorithms that solve the problem through iterative computation.
*Illustrative imageStatistical Mechanics of Compressed Sensing
The lab has provided a means of performance analysis, based on methods of statistical mechanics, for compressed sensing, which recovers signals from a small number of observations. Recently, it has extended the same approach to sparse modeling, a broader framework.
MembersFaculty
The members of the Kabashima Lab consist of faculty members and doctoral and master's students.As of 2026
- ProfessorYoshiyuki KabashimaPublications ↗
- Assistant ProfessorTakashi TakahashiPublications ↗
VoicesStudent voices
Compiled from answers by students who were in the lab. Ratings and reviews reflect individual students' experiences, not the lab's official views.
Students who take part in an interview may receive a thank-you gift worth ¥1,000, regardless of what they say.
On a 4-point scale, ● marks where students' answers fall
Who is this lab for?
What's great about this lab?
What did you learn after joining?
What's the vibe, and what is the professor like?
Where do graduates go?
RelatedLabs similar to Kabashima Lab
Theoretical Cosmology LabFaculty of Science, Department of PhysicsAstronomical object formation and exploration of the distant…
Suzuki LabFaculty of Science, Department of PhysicsTackling diverse problems in nuclear physics from the perspe…
Ito LabFaculty of Science, Department of PhysicsNonequilibrium statistical mechanics, biophysics, and theory…
Ueda LabFaculty of Science, Department of PhysicsQuantum measurement, quantum information, information thermo…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: “Magnetic domains of grain oriented silicon or electrical steel” Matesy / CC BY-SA 3.0 (cropped)
- Statistical Mechanics of Error-Correcting Codes: “Ising-tartan” Linas at English Wikipedia / CC BY-SA 3.0 (cropped)
- Detection of Mixed Communication Signals: “base stations in Réunion Island” Parchaco / CC0 (cropped)
- Statistical Mechanics of Compressed Sensing: “Extended Sparse Matrix” Yetanotherwikier / CC BY-SA 4.0 (cropped)
- Related lab (宇宙理論研究室): “Computer simulation of a Lyman-alpha Blob” J.Geach/D.Narayanan/R.Crain / CC BY 4.0 (cropped)
- Related lab (鈴木研究室): “RIKEN Superconducting Ring Cyclotron P4208172” Kestrel / CC BY-SA 4.0 (cropped)
- Related lab (伊藤(創祐)研究室): “Belousov Zhabotinsky reaction ( )” Stephen Morris / CC BY 2.0 (cropped)
- Related lab (上田 正仁 研究室): “JILA's strontium optical atomic clock” Sebastian Blatt, JILA, University of Colorado / Public domain (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.