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Research

My research interests lie at the intersection of three fairly broad areas of Computer Science: Artificial Intelligence, Biologically-Inspired Computing, and Distributed/Parallel Computing.

Most recently I have been examining the immune system for metaphors (bio-inspired) for the development of machine learning (AI) algorithms and looking at what can be gained by exploiting multiple-processors (distributed/parallel) in such algorithms. The latest stage in this investigation has been the development of a basic distributed version of the immune-inspired learning algorithm AIRS (Artificial Immune Recognition System). The use of distributed resources to explore local reactions and distributed behavior in immune-inspired systems is one area of interest to me.

I am also extremely interested in bio-inspired computing, in general, as well as other areas of "non-standard" computation. The way biological concepts can inspire the building of alternative computing architectures, can point toward the development of new problem-solving techniques, can allow for the exploration of emergent behavior in our systems, and so much more fascinates me. And just as thrilling is that our simulations, models, and metaphor-based computing can also help to inform our understanding of how the biological systems work.

Feel free to browse my publications for work I've done in this area (mostly immune-inspired supervised learning). And check out my collection of links to sites I've found useful in this work.