Jovan David Rebolledo-Mendez

Jovan Rebolledo has always loved exploring and manipulating various technologies and has enjoyed physics since he was a child. His academic interests and research have covered diverse subjects from robotics to adaptive systems and, most recently, bioinformatics. He earned his MS and PhD in engineering and computer science degrees from Kanazawa University in Japan. In addition to his academic work, he has professional experience as a software engineer for both a software company and a nuclear power plant. He finds language structures fascinating and currently speaks Japanese, French, and English in addition to his mother tongue, Spanish. In 2009 he spent the summer at the NASA Ames Research Park for the inaugural Singularity University Graduate Studies Program, where he had the opportunity to interact with and learn from a number of visionary tech leaders.

As a postdoctoral associate in the Department of Anatomical Sciences and Neurobiology at the University of Louisville, Jovan is currently working on a number of projects that apply artificial intelligence concepts to biological data for classification and prediction. He also has an interest in entrepreneurship and enjoys reading, doing yoga, nature, biking, salsa dancing, hiking, traveling, and learning new things.

Unscrambling Cellular Automaton Patterns

Currently, the use of microarray to characterize the gene expression is a technique vastly used. The goal of this project is to find the way to reconstruct the original rule of a CA that has been previously scrambled randomly by its columns. There exist different types of rules, and the objective is to find as many reconstruction rule methods as possible. Each type of rule requires a specific method. The final collection of reconstruction methods will be useful to use as a microarray classificatory system where a CA could be assigned to a specific microarray in order to propose a biomarker system of it.

Rule 582964