May 29, 2014, 6:00 AM —
As I wrote recently, U.S. college students aren’t exactly flocking to study computer science, despite the tremendous demand for tech workers (and the associated high salaries and generous benefits). However, computer science is still alive and well as a course of study, basically maintaining a steady percentage of U.S. undergraduate degrees. If you’re thinking of studying CS in college, or getting a graduate degree in it, you’ll be interested in a new study and data set recently released by researchers at Brown University.
Jeff Huang, an assistant professor of computer science at Brown, recently tasked students in his human-computer interaction seminar with crowdsourcing a study of CS faculty at 50 top colleges and universities in the United States. 19 students were each given $30 to hire people through Amazon Mechanical Turk to collect information on the CS faculty at 5 different schools such as faculty position (associate, assistant or full professor), year hired and primary field of research. In the end, they collected data on over 2,100 CS faculty members at 51 schools.
Huang and his students analyzed the data and shared their findings. Here are three things their data showed which I found interesting:
If you want to be a computer science professor, go to M.I.T.
When looking at where the faculty members got their PhDs from, M.I.T was the clear number one producer of computer science professors (it was also where most CS professors earned their bachelor degrees). This, of course, isn’t really surprising, given all that M.I.T. has contributed to computer science over the years. Still, it’s worth noting. Here are the five PhD programs that have produced the most CS professors:
Top PhD programs producing CS professors
|School||Number of professors|
|Massachusetts Institute of Technology||256|
|University of California - Berkeley||170|
|Carnegie Mellon University||121|
|University of Illinois at Urbana-Champaign||80|
Source: Brown University
If you want to study computer science theory, go to a private university
Each professor in the study was categorized based on his or her primary field of research into one of four areas: theory (e.g., algorithms, machine learning), systems (e.g., architecture, networking, programming languages), informatics (e.g., AI, data mining, graphics) and scientific computing. Huang then looked at the distribution of faculty research areas for each school. One strong finding jumped out.
“9 of the 10 most theory-heavy universities are private universities, whereas 9 of the 10 least theory-heavy universities are public.”
One explanation for this finding offered is that public universities are more engineering oriented while private universities are more science oriented. Is this related to a recent report by PayScale that found that computer science graduates from state schools generally got a better ROI on their college investments than those who studied CS at private schools? Perhaps these more practical, engineering-related skills are more valuable than pure computer science theory.
Computer science theory is still the dominant research area, but that might be changing
When looking at the breakdown of CS faculty hirings by research area, Huang and his students found that computer science theory is still the overall most dominant primary field of research, by a wide margin. Here are the top five fields of research:
Most popular fields of research
|Field of research||Number of professors|
|Algorithms & Theory||293|
|Hardware & Architecture||161|
|Networks & Communications||160|
|Bioinformatics & Computational Biology||134|
Source: Brown University
However, when looking at the fields of research of CS professor hires over time, the researchers found that there’s a sharp upward trend since 2010 in hiring professors who study systems and informatics, and a decline in the hiring of faculty members who study CS theory since 2011. Those are fairly short windows of time to say whether they are significant trends, so it will be interesting to see if they continue.
Huang points out that their data are still incomplete and they’ve asked for help in cleaning them up further. You can access their data in this Google spreadsheet and add your own contributions. Who knows? Maybe studying other computer scientists will someday become a field of research for computer scientists.
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