I am a physicist interested in quantum mechanics, statistical mechanics, musical set theory, music composition, natural language processing, symbolic and probabilistic artificial intelligence, and cognition. I have a B.S. in chemistry from UCLA, a Ph.D. in chemical physics from the University of Washington, Seattle, and a postdoctoral fellowship from UCSF. As of 2018, I have been developing and prototyping software algorithms for 28 years with applications in the physical sciences, bioinformatics, diagnostics, music composition, specialized areas of cognition, reasoning, associative memory, and natural language processing. I currently work in the defense industry, designing artificial intelligent systems, that predict human behavior and events.
Using techniques in artificial intelligence, I build human-like intelligent model systems that simulate actual reality, and use the properties and mathematics of quantum mechanics to describe systems and dynamics of artificial neural networks, especially for bidirectional associative memory. Some applications involve predicting human behavior, modeling the flow of liquids and micro-structure, pattern recognition, neural machine translation, and model systems for quantum cognition. Other applications involve using combinations of artificial intelligence, musical set theory, cyclic sets, and interval class vectors, to produce both tonal and atonal structured compositions.
I am active and associated with the following organizations: