What Faculty Hiring Reveals About the Prestige Network of Top CS Programs

TL;DR

This analysis looks at top U.S. computer science programs from the perspective of faculty origin: where current professors received their highest degrees.

The main finding is that the “Big Four” in CS: MIT, Stanford, CMU, and UC Berkeley, are not just strong in rankings. They also form the center of an elite faculty-hiring network. Top CS departments hire many faculty members who were trained at these four schools, especially MIT and Stanford, which appear to have the broadest national reach across the dataset.

At the same time, the data also shows that schools such as UIUC, University of Washington (UW Seattle), Georgia Tech, UT Austin, University of Michigan, Cornell, and Princeton have strong academic influence. They may not always be grouped with the Big Four, but their PhD graduates clearly appear in the faculty pipelines of top CS programs.

So the overall takeaway is simple:

CS prestige is not just a ranking list. It is a network.

The Big Four sit at the center of that network, but other research powerhouses also play an important role in shaping the academic world of computer science.

It has been a while since I posted my last blog about CS rankings on April 10, 2026. While I have been enjoying the happiness of becoming an upcoming freshman at UC Berkeley as a Computer Science major, I have also been digging further into the top CS programs in the United States.

This time, instead of looking only at rankings, I wanted to look at top CS programs from another perspective: faculty origin.

In other words, where did the faculty at top CS programs receive their highest degrees? If a department hires many professors trained at certain universities, that may tell us something about how top programs view each other academically.

Hopefully, this analysis can help young researchers and students think about their academic road ahead, especially if they are considering academia instead of industry.

When people talk about top computer science programs, they usually talk about rankings.

U.S. News has one list. CSRankings has another. Niche, College Factual, and other websites all create their own versions of what “top CS” means. In my earlier post, I wrote about how these rankings often measure different things: reputation, research output, student experience, selectivity, or some combination of all of them.

But there is another way to look at CS prestige that I find especially interesting:

Where did the faculty at top CS programs get their degrees?

Instead of asking how schools rank themselves or how external ranking systems evaluate them, we can ask a different question:

When elite CS departments hire professors, which doctoral programs do they seem to trust the most?

This gives us another lens into how top CS programs view each other.

For this analysis, I looked at a summary of faculty educational backgrounds from several top U.S. computer science departments. The data was extracted from each school’s official website as of May 29, 2026. For CMU, I only counted faculty from the Computer Science Department and the Machine Learning Department within the School of Computer Science. Since the data comes from public faculty profiles, it is not a complete record of every hiring decision. It does not show the full applicant pool, interview process, postdoc experience, or research fit behind each hire.

Still, it reveals something meaningful: the academic “pipeline” behind top CS faculty.

And the pattern is clear.

The Big Four Are Real

In computer science, people often refer to the “Big Four”: MIT, Stanford, Carnegie Mellon, and UC Berkeley.

These four schools are widely recognized as Tier 1 CS programs. Of course, exact rankings vary from year to year. In some rankings, CMU, MIT, and Stanford may be tied at the top, while Berkeley may be slightly lower. In other rankings, Berkeley may appear higher depending on the methodology. But the specific order is less important than the larger pattern.

These four schools consistently form the core of elite CS.

The faculty-degree data supports this idea strongly. Across the top CS departments in the dataset, MIT, Stanford, CMU, and Berkeley appear again and again as major sources of faculty training.

This is not just a rankings story. It is a hiring-network story.

Top CS departments are not only ranked highly by outsiders. They also seem to recognize each other as the strongest sources of future faculty.

A Prestige Loop Among Tier 1 Programs

The most striking trend is that Tier 1 schools tend to hire from each other.

MIT’s faculty origins are heavily concentrated in MIT, Stanford, Berkeley, and CMU. Berkeley’s are also heavily concentrated in Berkeley, Stanford, MIT, and CMU. Stanford and CMU show the same general pattern.

This creates what I would call a prestige loop.

The top programs produce PhD graduates. Other top programs hire them as faculty. Those faculty then train the next generation of PhD students, who may later become professors at other elite departments.

This cycle reinforces the academic status of these schools.

Among the schools in the dataset, the approximate share of faculty whose highest degree came from MIT, Stanford, CMU, or Berkeley was especially high at the Big Four themselves:

Target CS Program	Approximate Big Four Share
MIT	74.1%
UC Berkeley	68.4%
Stanford	56.2%
Carnegie Mellon	55.8%

This suggests that the Big Four are not just strong individually. They form a tightly connected ecosystem.

MIT and Berkeley show especially high Big Four concentration. Stanford and CMU are still strongly connected to the Big Four network, but their faculty origins appear slightly more distributed.

MIT and Stanford Have the Broadest Hiring Prestige

Another pattern is that MIT and Stanford appear to have the most universal prestige across the dataset.

MIT and Stanford show up in the top faculty-origin lists for every target school in the summary. CMU appears in nearly all of them, while Berkeley also appears very frequently.

This does not mean MIT and Stanford are “better” than Berkeley or CMU in every area. That would be too simplistic. CS is too broad for one ranking to capture everything. Different schools have different strengths in artificial intelligence, theory, systems, human-computer interaction, programming languages, robotics, and many other fields.

But from this faculty-origin perspective, MIT and Stanford seem to have the broadest national reach.

A PhD from MIT or Stanford appears to travel extremely well across top CS departments. CMU and Berkeley also have enormous prestige, but MIT and Stanford seem slightly more universally represented in this dataset.

The Second Layer of Elite CS Is Also Very Strong

The Big Four dominate the network, but they are not the whole story.

Schools like UIUC, University of Washington (UW Seattle), Cornell, Princeton, Georgia Tech, UT Austin, and University of Michigan also appear as important faculty pipelines.

This matters because it complicates the simple prestige narrative.

If we only looked at a traditional reputation ranking, we might focus too much on the very top few schools. But faculty hiring shows that many other research-intensive CS departments also have real academic influence.

For example, UIUC appears as a major source in several departments. Georgia Tech and University of Washington (UW Seattle) also show strong self-pipeline effects. Michigan, UT Austin, Cornell, and Princeton each show up as important contributors in the broader network.

This connects to one of the main points from my earlier CS rankings post: different ranking systems capture different aspects of strength.

U.S. News is heavily reputation-driven. CSRankings focuses more on faculty research output. Niche and other undergraduate-focused rankings may emphasize student experience, outcomes, or campus life.

Faculty hiring gives us another dimension: peer recognition through doctoral training.

A school’s faculty-degree footprint tells us how much other departments seem to value its PhD graduates.

Self-Pipeline Is Another Important Signal

Another interesting pattern is self-hiring or self-pipeline strength.

Many top CS programs have a significant number of faculty who received their highest degree from the same institution. MIT, Berkeley, CMU, Stanford, University of Washington (UW Seattle), UIUC, Michigan, Georgia Tech, UT Austin, Cornell, and Princeton all show this pattern to varying degrees.

MIT and Berkeley stand out the most.

Target School	Approximate Self-Origin Share
MIT	29.6%
UC Berkeley	24.8%
UT Austin	19.3%
CMU	18.9%
University of Michigan	18.0%
Stanford	16.9%
University of Washington (UW Seattle)	16.3%

This does not necessarily mean these schools are directly hiring their own PhD students immediately after graduation. In many cases, a faculty member may earn a PhD from one school, work elsewhere, and later return.

Still, a high self-origin share suggests that a department strongly values its own doctoral training culture.

It also shows how elite academic communities can reproduce themselves over time.

What This Says About CS Prestige

To me, the main takeaway is that CS prestige is not just about a single ranking number.

A school’s reputation is shaped by multiple layers:

Peer reputation
Research output
Faculty hiring networks
Doctoral training strength
Undergraduate experience
Industry and graduate-school outcomes

The Big Four are powerful because they perform well across many of these dimensions. They are highly ranked, highly productive, and deeply embedded in the faculty hiring networks of other top programs.

But other schools also show major strength. UIUC, University of Washington (UW Seattle), Georgia Tech, UT Austin, Michigan, Cornell, and Princeton are not simply “below” the Big Four. They are major research institutions with their own hiring influence.

This is why I think CS rankings should be read carefully.

A ranking may say one school is #1 and another is #5, but the real academic world is more networked than linear. Prestige is not just a ladder. It is also a map.

My Overall Interpretation

The faculty-degree data shows that elite computer science hiring is strongly shaped by doctoral prestige networks.

MIT, Stanford, CMU, and UC Berkeley form the core of this network. Among them, MIT and Stanford appear to have the broadest representation across top departments, while CMU and Berkeley remain central members of the same Tier 1 ecosystem.

At the same time, the data also shows that research-intensive programs such as UIUC, Georgia Tech, University of Washington (UW Seattle), UT Austin, Michigan, Cornell, and Princeton have significant influence. These schools may not always be grouped with the Big Four in casual conversations, but their PhD graduates are clearly part of the elite CS faculty pipeline.

So the best conclusion is not simply that “the Big Four dominate,” even though they clearly do.

The more interesting conclusion is this:

Top CS faculty hiring reflects a prestige network, not just a ranking list.

The Big Four sit at the center of that network, but the surrounding research powerhouses also play an important role. Together, they reveal how top CS departments actually recognize, reproduce, and reinforce academic prestige.

For students who are thinking about an academic path, this matters. If someone wants to become a professor or researcher in computer science, the department where they receive doctoral training may shape not only their education, but also how they are viewed in the broader academic job market.

That does not mean only a few schools matter. Strong research can come from many places. But the faculty-origin data does show that academia has networks, and those networks are not random.

Understanding those networks can help students make more informed decisions about graduate school, research direction, and long-term academic goals.

Appendix

5,995 hits

May 29, 2026 0

CS Rankings and My College Application

Recently, I have been researching U.S. college computer science programs as part of my college application process. Now that the application season has mostly wrapped up, I wanted to put some of that research into one post and share both what I found and how I ended up thinking about these rankings.

When people talk about the “best” CS schools, they often sound like there is one clear answer. But after looking more closely, I do not think that is really true. Different rankings measure different things. Some focus more on academic reputation. Others emphasize research output. Others try to capture what it is actually like to be a student there. That means a school can look very different depending on which ranking you are looking at.

In this post, I want to go through three popular rankings with a focus on computer science: U.S. News, CSRankings, and Niche. I will also end with a short reflection on my own college application results and what this process has made me think about rankings more broadly.

U.S. News and World Report Ranking

U.S. News and World Report is probably the ranking that gets cited most often in general college conversations. It has a lot of influence, and for many families, it is the first place they look when trying to get a sense of how schools compare.

Its latest graduate computer science ranking for 2026 covers programs that awarded at least five doctoral degrees during the most recent five-year period available in summer 2025, which was 2020 to 2024, and includes 205 programs in total.

Below is the list of Top 20 graduate schools in 2026.

Rank | School (2026)
1 Carnegie Mellon University, MIT, Stanford
4 University of California – Berkeley
5 University of Illinois – Urbana-Champaign
6 Princeton
7 Cornell, Georgia Institute of Technology, University of Washington – Seattle
10 University of Texas – Austin
11 University of Michigan – Ann Arbor
12 California Institute of Technology, University of California – San Diego, University of Maryland – College Park
15 Columbia University, Purdue University – West Lafayette, UCLA, University of Wisconsin – Madison
19 Harvard, University of Pennsylvania

As a comparison, here is the list of Top 20 graduate schools in 2025.

Rank | School (2025)
1 MIT
2 Carnegie Mellon University, Stanford, University of California – Berkeley
5 University of Illinois – Urbana-Champaign
6 Georgia Institute of Technology
7 Cornell, Princeton, University of Texas – Austin, University of Washington – Seattle
11 University of Michigan – Ann Arbor
12 California Institute of Technology
13 Columbia University, University of California – San Diego, University of Wisconsin – Madison
16 UCLA, University of Maryland – College Park, University of Pennsylvania
19 Harvard, Purdue University – West Lafayette

Looking at the two years side by side, what stands out to me is that the overall group of schools near the top remains pretty stable even if the exact order changes. That matters because it suggests that people probably put too much weight on small year-to-year shifts. A school moving up or down a few spots may say less about a dramatic change in quality and more about the limits of ranking systems themselves.

As a graduating high school student, though, I found the undergraduate CS ranking more directly relevant.

Rank | School (2026)
1 MIT
2 Carnegie Mellon University, Stanford, University of California – Berkeley
5 Georgia Institute of Technology
6 Princeton
7 Cornell, University of Illinois – Urbana-Champaign
9 California Institute of Technology, University of Texas – Austin, University of Washington – Seattle
12 Harvard, University of California – San Diego, University of Michigan – Ann Arbor
15 UCLA
16 Columbia University, Johns Hopkins, Purdue University – West Lafayette, University of Maryland – College Park, University of Pennsylvania, USC, University of Wisconsin – Madison, Yale

A common criticism of the U.S. News undergraduate CS ranking is that it depends heavily on peer reputation. In other words, it reflects how academics and administrators view these programs, but not necessarily how strong they are in research output, placement, or undergraduate student outcomes. That does not make it useless. It just means it is one lens, not the final word.

CSRankings Ranking

CSRankings works very differently. Rather than relying mainly on reputation surveys, it is a metrics-based ranking built around faculty publications at selective conferences. That makes it especially interesting for students who care about research.

Many people in computer science see it as one of the more useful ways to evaluate research-oriented programs because it is harder to game and is tied more directly to where influential research is actually being produced.

Below is the snapshot from 2015 to 2025 that I included in my draft.

Rank | School
1 Carnegie Mellon University
2 University of Illinois – Urbana-Champaign
3 University of California – San Diego
4 Georgia Institute of Technology
5 MIT
6 University of Michigan – Ann Arbor
7 University of Washington – Seattle
8 University of California – Berkeley
9 Cornell
10 University of Maryland – College Park
11 Northeastern University
12 Stanford
13 Purdue University
14 University of Texas – Austin
15 New York University, University of Wisconsin – Madison
17 Princeton
18 University of Pennsylvania
19 Columbia University
20 UCLA

What I find useful about CSRankings is that it often complicates the more familiar prestige narrative. Schools that are not always placed at the very top in general public rankings can do extremely well here because of their research productivity. If your priority is faculty strength, publication volume, and the broader research ecosystem, this ranking can tell you something important that broader rankings do not.

At the same time, CSRankings also has clear limits. It is better at telling you where research is happening than at telling you what it feels like to be an undergraduate there. It does not really measure student life, advising quality, flexibility, or overall campus environment. So again, it is useful, but only if you know what question you are using it to answer.

Niche Ranking

Niche is different from both U.S. News and CSRankings because it is much more student-centered. It combines student and alumni reviews with data from sources like the U.S. Department of Education, and it tries to provide a broader picture of the college experience.

Unlike reputation-based or research-output-focused rankings, Niche tries to evaluate academics alongside student life, value, diversity, campus culture, food, dorms, and more. That makes it a more consumer-oriented ranking, but also one that may be especially relevant to students thinking about where they actually want to spend four years.

Below is the list of Niche 2026 Best Colleges for Computer Science.

Rank | School (2026)
1 MIT
2 Stanford
3 Carnegie Mellon University
4 California Institute of Technology
5 Columbia University
6 Yale
7 Harvard
8 Georgia Institute of Technology
9 Brown University
10 Cornell
11 Vanderbilt University
12 Princeton
13 Dartmouth College
14 University of Michigan – Ann Arbor
15 Duke University
16 University of Pennsylvania
17 Rice University
18 Harvey Mudd College
19 University of Texas – Austin
20 University of Chicago

What stands out here is that Niche values a broader undergraduate experience. That can produce results that feel very different from research-based rankings. A school may not dominate in CSRankings but still rank extremely well here because students value the campus culture, quality of life, and overall experience.

I think that is an important reminder. Students do not attend rankings. They attend schools. And the day-to-day reality of a place can matter just as much as the reputation attached to it.

What these rankings really measure

After looking through all three systems, my biggest takeaway is that rankings are most useful when you understand what they are actually measuring.

If you care most about research, then a publication-based ranking like CSRankings may be more informative. If you care about broad academic reputation, then U.S. News may matter more. If you care about the undergraduate experience in a wider sense, then Niche may tell you something the others miss.

That is why I do not think there is one “correct” ranking of computer science programs. Different rankings are answering different questions. The real mistake is treating them as if they are all measuring the same thing.

Once you start looking at schools that appear again and again near the top, the more meaningful differences often become less about rank and more about fit. What kind of research environment does the school have? What kind of advising and flexibility does it offer? What kind of student culture does it create? Those questions are harder to reduce to a number, but they may matter more in the end.

My college application outcome

In the 2025–2026 application season, I was fortunate to be admitted to two undergraduate CS programs ranked in the top 5, three ranked 6-10, and two ranked 11-15 in the 2026 U.S. News undergraduate computer science rankings. I will be visiting colleges with my family over spring break and deciding where to commit before the May 1st, 2026 deadline. In the meantime, I was also placed on a few waitlists at top CS programs, so part of the process is still continuing.

This whole process has made rankings feel both useful and limited to me. They are useful because they give you a way to organize a complicated landscape. They help show broad patterns and highlight different strengths across schools. But they are also limited because, once you get to a certain level, the differences between schools can be smaller and more context-dependent than the rankings make them seem.

For me, the more important question now is not just which school is ranked slightly higher. It is which one feels like the best environment for the kind of student and researcher I want to become.

Update: On May 8, 2026, I was accepted to UC Berkeley.

5,995 hits

April 10, 2026 0