by Jimmy Lin (University of Waterloo)
Obviously, research contributions cannot be entirely quantified via bibliometric statistics, which are known to be flawed in many ways (including systematic biases). On the other hand, they do serve as one (of many) signals, however noisy. Here, I provide that signal.
These are lists of computer science faculty with profiles in DBLP. For alignment, I use the same definitions (areas and conferences) as CSRankings. Due to different data processing scripts (from the source, DBLP), correspondence between the people that appear in CSRankings and these lists is only approximate. However, the information provided is complementary, as the focus of CSRankings is on institutions, whereas I focus on individuals here. These lists can be reasonably interpreted as, "I am interested in X, these are potential faculty who might be good advisors". Of course, the lists are not exhaustive, and there may be various reasons why a suitable advisor might not be on these lists.
These lists are compiled by me in a ad hoc manner, best characterized as snowball sampling (i.e., if I come across a name, I add to the list). I use a fairly simple test for inclusion: self identification. That is, if a researcher uses a particular keyword (or any reasonable variant) on their profile, they get included in the discipline-specific lists. I'm always looking to expand the lists and welcome additional contributions!
In an academic context, 大牛 🐮 (Dà niú), literally "big cow", refers to a famous professor. It is quite linguistically productive, e.g., "多牛?" (lit. "how cow(-ish)?"), translation: "how famous (is your professor)?"
— Jimmy Lin (@lintool) January 13, 2021
Yes, I know, the earliest year of publication is often wrong.