Office: 337 Ruffner
Dept of Math and Computer Science
201 High St
Farmville, VA 23909
My main field of research is Natural Language Processing. Within that area, I've done work in fast parsing and function tagging; I've written several papers in these areas. In addition, I am generally interested in various forms of syntactic analysis, machine translation, and voice recognition. My PhD work was in function tagging: specifically, on trying different machine learning methods and a variety of different linguistic features to improve our performance on the task. My function tagger is available on my research page.
A secondary research field is in Natural Language Semantics. I completed a master's degree in this field, with a thesis on the problem of distributivity and plurality in natural language predicates.
While I don't do research in the field, I am also interested in developments in the field of programming languages---there are some interesting parallels between the semantics we devise for our programming languages and that already exist in our natural languages, and some fascinating work is being done in this area.
Finally, I have an interest in the pedagogy of introductory computer science. In summer of 2002, I helped out with the Providence instantiation of the TeachScheme! seminar, an initiative to make computer science more widely acknowledged as an important part of a well-rounded education, even (and especially) at the high school level. Prior to that, I helped develop a new introductory CS class at Brown (CS 17/18, still being taught), predicated on the notion that a proper introduction to computer science is not simply a programming class, but a class in problem solving, design, and analysis as well. These are ideas I had already incorporated (with moderate success) into an introductory CS class taught in Java over at Knox; now I'm able to teach the curriculum more directly, as Monmouth explicitly follows the HtDP model.