Stony Brook Computer Science ranks well in recent NRC survey |
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The Stony Brook University Computer Science department has made a strong showing in the recently released NRC ranking, claiming a consistent spot in the top 20 of the Nation's Computer Science departments.
In October 2010, the National Research Council (NRC) released its long awaited survey of doctoral programs, based on data collected in 2006, and our department has ranked very well. By most important and specific metrics, we rank repeatedly from 15th to 24th compared to other U.S. doctoral programs; these rankings are for important measures such as overall quality, research productivity, publications, and student support and outcomes. The NRC ranking is considered the "gold standard" of academic rankings. It is more comprehensive and objective of the academic performance of a department and its members than other popular, subjective rankings, such as those published by US News & World Report.
The following two tables show the top 20 US computer science departments (out of 126 surveyed) for both evaluation measures: survey and regression. Stony Brook has been consistently ranked amongst the top Ivy Leagues, such as, Princeton, Cornell, Harvard, University of Pennsylvania, and Columbia University, as well as other schools considered Ivy League-class, such as University of California, Carnegie Mellon, Duke, and others. The two charts show a composite measure of research productivity, student support and outcomes, the first survey-based, the second regression-based.
Survey-based:| # | Rank | Program |
|---|---|---|
| 1 | 1-2 | Stanford University Computer Science |
| 2 | 1-4 | Princeton University Computer Science |
| 3 | 2-15 | Massachusetts Institute of Technology Computer Science |
| 4 | 2-15 | Harvard University DEAS-Computer Sciences |
| 5 | 3-18 | University of California-Berkeley Computer Science |
| 6 | 3-18 | University of California-Santa Barbara Computer Science |
| 7 | 3-22 | University of Pennsylvannia Computer and Information Science-SEAS |
| 8 | 4-24 | Cornell University Computer Science |
| 9 | 4-32 | Carnegie Mellon University Computer Sciences |
| 10 | 5-30 | Columbia University in the City of New York Computer Science |
| 11 | 5-30 | Duke University Computer Science |
| 12 | 5-38 | University of California-Riverside Computer Science |
| 13 | 6-38 | University of California-San Diego Computer Science and Engineering |
| 14 | 5-38 | University of North Carolina at Chapel Hill Computer Science |
| 15 | 7-37 | University of California-Los Angeles Computer Science |
| 16 | 7-46 | Stony Brook University Computer Science |
| 17 | 6-45 | University of Maryland-College Park Computer Science |
| 18 | 8-48 | University of Wisconsin-Madison Computer Sciences |
| 19 | 7-46 | University of Rochester Computer Science |
| 20 | 8-48 | University of Illinois at Urbana-Champaign Computer Science |
Regression-based:
| # | Rank | Program |
|---|---|---|
| 1 | 1-2 | Stanford University Computer Science |
| 2 | 1-4 | Princeton University Computer Science |
| 3 | 1-5 | Massachusetts Institute of Technology Computer Science |
| 4 | 3-11 | Cornell University DEAS-Computer Science |
| 5 | 3-11 | University of California-Berkeley Computer Science |
| 6 | 4-15 | University of California-Santa Barbara Computer Science |
| 7 | 4-15 | Carnegie Mellon University Computer Sciences |
| 8 | 4-18 | Harvard University DEAS-Computer Sciences |
| 9 | 4-17 | University of Pennsylvania Computer and Information Science-SEAS |
| 10 | 5-20 | University of Rochester Computer Science |
| 11 | 6-21 | University of North Carolina at Chapel Hill Computer Science |
| 12 | 6-25 | University of Illinois at Urbana-Champaign Computer Science |
| 13 | 8-28 | University of California-San Diego Computer Science and Engineering |
| 14 | 8-30 | University of Maryland-College Park Computer Science |
| 15 | 8-38 | University of California-Riverside Computer Science |
| 16 | 10-33 | Duke University Computer Science |
| 17 | 10-37 | Stony Brook University Computer Science |
| 18 | 10-38 | University of Wisconsin-Madison Computer Sciences |
| 19 | 12-43 | Columbia University in the City of New York Computer Science |
| 20 | 12-38 | University of California-Los Angeles Computer Science |
The data were obtained using the tools provided at phds.org on 12/11/2010. To obtain these tables we equally weighted research productivity and student outcomes with the highest weight and then either applied the highest weight to survey-based or regression-based.
The NRC ranking considers two main overall ranking schemes: Survey-based and Regression-based. Both measures use the same data on 20 key variables but they use different methods to determine which variables are the most important predictors of program quality. Some of these key variables are:
- publications per faculty member,
- average citations per publication,
- percent of faculty with grants,
- percent of students with full support in first year of study,
- percent of international students,
- average annual PhDs graduated,
- median time-to-degree for full- and part-time students,
- individual workspace for students,
- and others.
For the Survey-based measure, the relative weight of each variable is directly based on input from about 50 faculty members in each field. Each faculty member was asked to identify the most relevant variables in assessing program quality and to give each one a numeric value according to its importance. These weights were then used to rank the doctoral programs.
For the Regression-based measure, instead of asking evaluators to state what factors they believe to be most important, the survey panel asked faculty members to rate a selection of doctoral programs, then looked at which characteristics of the rated programs correlated most strongly with high or low scores. In each discipline, about 50 faculty members rated a random selection of 15 programs on a scale of 1 to 6, without stating the criteria they applied in judging the programs. Based on these ratings, regression analysis was employed to calculate the weights to be used for ranking.
Research productivity is based on the following:- publications per faculty member,
- citations per publication,
- percent of faculty holding grants,
- awards per faculty member
Student outcomes include:
- 6-year graduation rates,
- time to degree,
- job placement within academia,
- percentage of first-year students with full financial support and whether a program collects data about the employment outcomes of its graduates.
Article created on: November 2010