• E-mail: maclennan@utk.edu

Education

• BS in Mathematics (with Honors), Florida State University, 1972
• MS in Computer Science, Purdue University, 1974
• PhD in Computer Science, Purdue University, 1975

MacLennan joined Intel Corporation in 1975 where, as a Senior Software Engineer, he participated in the architectural design of the 8086 and the iAPX-432 microprocessors. In 1979 he returned to academia, joining the Computer Science faculty of the Naval Postgraduate School (Monterey, CA), where he was assistant professor (1979-83), associate professor (1983-87), and Acting Chair (1984-85). At NPS he investigated novel models for massively parallel computing and artificial intelligence. Since 1987 he has been an associate professor of electrical engineering and computer Science at UT.

In the mid-’80s, MacLennan redirected his research toward natural computation, that is, computation inspired by or occurring in nature. One goal has been to understand the representation and processing of information in the brains of humans and other animals and to investigate brain-inspired computing technologies. This work is especially relevant to AI, but also to neuroscience, cognitive science, and philosophy, and so he is active in the interdisciplinary intersection of these research areas and collaborates with scholars in each of them.

Since the mid-’90s this research program has expanded to include self-organizing systems with very large numbers of physical components (e.g., the cells in a developing embryo) and the interaction of physical and computational processes. The latter includes the use of computational principles in nanotechnology (algorithmic self-assembly) and the exploitation of novel physical processes for computation (post-Moore’s Law computing technologies).

MacLennan has 100 refereed journal articles and book chapters, has authored two books (one in its third edition), and edited a third. In 2008, MacLennan was invited to become the founding Editor-in-Chief of the “International Journal of Nanotechnology and Molecular Computation.”

• Bio-inspired Computation
• Self-organization
• Algorithmic Nano-assembly
• Artificial Morphogenesis