Professor Sarria’s research involves developing new constraint programming languages based on process calculi, exploring novel teaching/learning methodologies for computer science materials, and developing new theories and tools for solving problems in Security Protocols, Biology and Multimedia Semantic Interaction. He is currently applying artificial intelligence techniques at the intersection of machine learning, pattern recognition and data mining for Computational Characterization of Salsa Music. He is developing a novel approach to perform data mining on a big set of Salsa songs to build a system that models this musical genre and recognizes and classifies them using machine-learning techniques. He has contributed new constraint programming software solutions for enterprises, including the programming language Cordial, and most recently formal models of time musical processes that are currently being applied to characterize, understand and classify musical genres (particularly Salsa).
Currently Funded Research
Computational Characterization of Salsa Music, a project funded by three universities in Cali, Colombia. An approach to perform data mining on a big set of songs and thus to built a system that models this musical genre and recognizes and classifies old and new Salsa songs using machine learning techniques.