Juan Arturo is working on his doctoral dissertation on machine learning using quantum algorithms at the Instituto Tecnológico y de Estudios Superiores de Monterrey (ITESM). He has taught many undergraduate courses at ITESM, Universidad Nacional Autónoma de México (UNAM), and Universidad Anáhuac Querétaro, including quantum computing, complex variables, differential equations, calculus, data mining, and machine learning. He has done research at UNAM in the fields of optics and group theory. [AliasDelimiter]He is looking forward to working with many people with similar interests and different backgrounds and cultures at the Wolfram Science Summer School.
Project: Logical Operations on Cellular Automata
Cellular automata (CA) have been extensively studied, and some of the rules that generate CA are known to produce complex behavior, while others produce nested and/or periodic patterns. One common way to process a cellular automaton pattern is to collect cells together into small groups, and then to calculate the median value of the cells in each group. This process is often called coarse-graining. In the present work we study generalizations of coarse-graining, where arbitrary Boolean functions (rather than the median operation) are used to process the values of cells in each group. We will inspect the resulting patterns and look for potential regularities where there was complex behavior in the original CA.