PhD-application-related reflection

[gusl]

This is from an email conversation with a professor (who I will leave anonymous for now, by default):

<< I like the idea of making Machine Learning a tool usable by "the scientists", by doing model search with a prior that encodes the scientist's domain knowledge. This isn't always very straightforward, but I'd like to work on making it so... I gravitate around knowledge engineering when confronting this kind of question.

While I can get very excited by the idea of "automated science", I am in practice more fond of the engineering ideology. I'm really only satisfied when I have a program that works. I suppose at one level, it's as if I were a stupid person who is skeptical of abstract arguments: even as a math major, I leaned very experimental. (I think this is the same skepticism that led me to my interest in mathematics formalization systems, which turned out to be completely impractical, and very painful and unrewarding to work with. That's a different long-term dream.) >>
-Gustavo Lacerda