QS ranking profile
Keio University
This page presents clearly labeled QS ranking data for orientation. It does not verify programs, supervisors, funding, admission requirements, or the university's website.
- QS 2026 rank
- #215
- Down 27 places since 2025
- QS 2025 rank
- #188
- Overall score
- 54.5
Explore opportunities at Keio University
Browse active research positions, doctoral fellowships, and university funding calls indexed from official faculties and verified sources.
QS indicators
Reported ranking indicators
Each indicator is scored out of 100 in the same QS snapshot as the summary above.
#153 worldwide
#57 worldwide
#268 worldwide
#801 worldwide
#801 worldwide
#735 worldwide
#674 worldwide
#759 worldwide
#71 worldwide
#331 worldwide
Institution profile
How QS classifies this institution
QS groups institutions by size, subject range, and research output.
- Size
- Extra large
- More than 30,000 students
- Subject range
- Focused
- Teaches a limited range of faculty areas
- Research intensity
- Very high
- Very high research output in the QS classification
- Region
- Asia
- QS regional grouping
University profile
About Keio University
Editorial background written for orientation. Verify programs, funding, and admission on the university's official pages.
Faculty, graduate-school, and institute layers make Keio research easier to locate
Keio University presents research across undergraduate faculties, graduate schools, research institutes, and centres. Its public research material explicitly frames these as parts of a broad interdisciplinary environment rather than as one uniform setting. That matters when a topic carries more than one disciplinary label. A data question can take a technical, social, legal, health, or business direction. A biomedical question may require a laboratory context as well as a clinical or computational one. The university-level structure is useful for identifying possible routes, but it cannot determine the right one without a smaller page that names the research problem and the group working on it.
The different layers also answer different questions. A faculty can show the disciplinary base. A graduate school can clarify how a field is organised at an advanced level. An institute or centre can reveal a recurring research community that may cross department boundaries. None of these pages establishes a current project simply by existing. A profile becomes more credible when it separates these roles and connects the topic to a specific method, material, dataset, population, or system. Keio University's public map can then provide a useful frame around that direct evidence instead of substituting for it.
Cross-disciplinary research and social implementation are distinct public routes
Keio's research page highlights cross-disciplinary research, problem-solving, social implementation, and collaboration across research initiatives. These ideas can be useful for understanding how a topic might extend beyond a single discipline. They should be read with care. Social implementation is not a generic feature of every laboratory, and cross-disciplinary work is not established merely because two departments share a keyword. The relevant local material needs to show what is being studied, how the work is done, and where a second discipline or external context becomes necessary. That keeps a wide research mission from being mistaken for a project description.
This is particularly important for questions that are both technical and societal. A digital system may involve computer science but also law, management, health, or human behaviour. A life-science problem may require experimental work while also involving data analysis or an interface with a health setting. Rather than assuming a connection from the university's overall language, record the chain in order: research object, primary method, academic home, and any visible collaborating setting. Keio's public research structure offers places to look for that chain, including faculties, graduate schools, institutes, centres, and research-support routes.
Use a Keio University comparison to distinguish an academic home from a wider network
For Keio University, write the research question before choosing a faculty or centre. Identify whether the key evidence is a codebase, an experiment, a biological sample, a social dataset, a legal source, a material, or an organisational practice. Then find the unit that publicly links itself to that evidence. If a centre or cross-disciplinary initiative is relevant, explain its role separately from the primary academic home. This provides a compact account of how the subject might be approached without treating a broad institutional arrangement as proof of a particular research pathway.
A final check can name the most important uncertainty. An institute may clearly match the field but not show the current team. A faculty can establish the disciplinary setting while leaving the exact method unresolved. A collaboration route can be visible at university level without demonstrating its place in one line of work. These limits are helpful because they show where a closer local reading is needed. Keio University makes several research layers public, from faculties and graduate schools to institutes, centres, and cross-disciplinary initiatives. A focused evidence chain turns those layers into a realistic comparison of one academic setting.