Paul Bodily

Bio

Professor Bodily joined ISU in the Fall of 2018 as an Assistant Professor of Computer Science. His research addresses the question of whether or not computers can exhibit autonomous creativity, focusing particularly on the domain of lyrical music composition and the challenge of global structure. His approach incorporates a modular machine learning framework called hierarchical Bayesian program learning, which facilitates breaking the problem of music composition into smaller pieces, and focuses primarily on developing machine learning models that solve the problems related to structure. He has developed an adaptation of non-homogeneous Markov models that enables long-range constraints and a structural learning model adapted from the Smith-Waterman alignment method, which extends sequence alignment techniques from bioinformatics. He has incorporated these advances into a full-fledged computational creative system called Pop* (pronounced pop star) and has shown through various evaluative methods that the system can be argued to possess, to varying degrees, the characteristics of creativity. Professor Bodily's prior research also includes several bioinformatics publications on heterozygous genome assembly algorithms.

 

Dr. Bodily holds a Ph.D. and M.S. in Computer Science from Brigham Young University (BYU). He graduated summa cum laude from BYU with a B.S. in Bioinformatics, a B.A. in Italian, and minors in Computer Science and Music. Dr. Bodily has an extensive music background as a composer and performer. In addition to playing several instruments, he is an alumnus of BYU’s 9-man internationally-renowned acappella group, Vocal Point.

Research Interests

Computational Creativity, Bioinformatics, Artificial Intelligence, Machine Learning, Natural Language Processing

Teaching Interests

Artificial Intelligence, Theory of Computation, Algorithms, Machine Learning, Natural Language Processing, Computational Creativity