David Doty



Contact Information

Assistant Professor
Department of Computer Science
University of California, Davis

Office: 3039 Kemper Hall

Mailing Address:
Department of Computer Science
University of California
One Shields Ave.
Davis, CA 95616, USA

Research Interests

I am broadly interested in problems at the intersection of physics, chemistry, biology, and computation. By this I do not mean the traditional "computation in service of natural science" (e.g., bioinformatics, computational chemistry, or molecular dynamics simulation). Rather, certain molecular systems — such as a test tube of reacting chemicals, a genetic regulatory network, or a growing crystal — can be interpreted as doing computation themselves. I want to understand the fundamental logical and physical limits to computation by such means.

I have worked in algorithmic self-assembly, such as the tile assembly model developed by Erik Winfree, and computation using chemical reactions. DNA nanotechnology, pioneered by Ned Seeman, is a field focused on using artificial DNA strands to assemble nanoscale structures and dynamic systems such as logical circuits. Experimental work in that field informs many of the questions that interest me.

Furthermore, there are deep connections between realistic physical models and existing models of computation. For example, chemical reaction networks are related to a model of distributed computing known as population protocols (as well as an older model of concurrent processes known as Petri nets), and the tile assembly model has connections to Wang tiling and cellular automata.

Formerly (and possibly in the future) I studied methods of measuring information and the extent to which computation on objects is capable of altering their information content. My research in this direction is in an area in which theoretical computer science intersects with fractal geometry and information theory, known as effective fractal dimension, developed by Jack Lutz. I am also interested in another area known as computational depth, which is a different notion of algorithmic information developed by Charles Bennett.

Teaching