My research interests revolve around various reasoning and representation problems in Artificial Intelligence. My main foci these days include CSPs (constraint satisfaction problems), planning, SAT (satisfiability), Bayesian Inference, and Constraint Optimization Problems. I am interested in developing algorithms for these problems that can achieve better performance by taking advantage of domain specific knowledge or structure. This can sometimes entail developing formalisms for representing such knowledge.
For example, F. Kabanza and I developed an approach whereby extra domain specific knowledge can be represented declaratively and used to solve planning problems. Our approach can obtain orders of magnitude increases in performance from very simple domain knowledge. The TLPlan planning system, developed with M. Ady, utilized this approach to planning and demonstrated its effectiveness by winning the AIPS2002 international planning competition.
Another example is my 2clseq SAT solver which utilizes extensive binary clause reasoning exploiting the "binary substructure" of a clausal theory. When run as a preprocessor this kind of reasoning greatly simplifies clausal theories, sometimes converting problems unsolvable by current SAT solvers into problems they can easily solve.
On-Line versions of most of my papers are available under the Research tab. This area also contains some on-line tutorial material and talk presentations. My research has also yielded a number of software systems some of which are available under the Software tab. Under the Teaching tab you will find various materials I and others have created for teaching with links to some of the courses I teach.
Finally, I have been involved in the organization of a number of academic conferences. Under the Conferences tab you will find links to previous conferences I have been involved in.