The university where I work asks us to register all our publications for the year in a central database . Doing this obviously made me think of doing an ego search on my academic papers. Plus, it’s the beginning of the year, which always seems like a good time to look at these things.
The handy tool Publish-or-Perish calculates all sorts of citation metrics based on a search of Google Scholar. The tool lets you pick the set of publications to consider. (For example, I left out all the publications from another Paul Groth who’s a professor of architecture at Berkeley.) I did a cursory run through to remove publications that weren’t mine but I didn’t spend much time so all the standard disclaimers apply. There may be duplicates, it includes technical reports, etc. For transparency, you can find the set of publications considered in the Excel file here. Also, it’s worth noting that the Google Scholar corpus has it’s own problems, in particular, it makes you look better. With all that in mind, let’s get to the fun stuff.
My stats as of Jan. 4, 2011 are:
You can find the definitions for these metrics here.
What does it all mean? I don’t know 🙂 I think it’s not half bad.
For comparison, here’s a list of the h-indexes for top computer scientist computed using Google Scholar. All have an h-index of 40 or greater. A quick scan through that least, shows that there’s a pretty strong correlation between being a top computer scientist and a high h-index. Thus, I conclude that I should continue concentrating on being a good computer scientists and the statistics will follow.
 I don’t know why my university doesn’t support importing publication information from bibtex, or RIS. Everything has to be added by hand, which takes a bit.