EURO 2018 Keynote Video

A performance at QMUL's Guest Night led to Professor Greet Vanden Berghe discovering my work at the intersection of OR amd Music, and consequently an invitation to give a keynote talk at EURO 2018, the largest European Conference for Operational Research and Management Science.

Program Chair, Professor Vanden Berghe ensured the conference featured a gender-balanced array of plenary and keynote speakers covering a wide variety of topics related to Operational Research. General Chairs, Professor Rubén Ruiz and Professor Ramón Álvarez-Valdés, kept up an impressive environmentally and socially conscious agenda at the conference while ensuring the attendees were treated to the spectacular architectural gems at the City of Arts and Sciences in Valencia.

Official photos and videos from conference can be found at euro2018valencia.com/photos_videos. The directory of plenaries and keynotes has also been updated with the videos of each talk at euro2018valencia.com/plenaries-and-key-notes . The video of my keynote is re-posted below.

Keynote: [ Tweets & Photos ]

Keynote: Optimization and Music Data Science

Place: Universitat Politècnica de València (Nexus Building)
Date: Monday, July 9 10:30-12:00



Abstract: The explosion in digital music information has spurred the developing of mathematical models and computational algorithms for accurate, efficient, and scalable processing of music information. According to the 2017 IFPI Industry Global Music Report, the total global recorded music revenue was US$15.7b in 2016, 50% of which were digital. Industrial scale applications linking recorded content to listeners include Last.fm, Pandora, Shazam, and Spotify. Shazam has over 120 million active users monthly and Spotify over 140 million. Since the launch of Shazam, users have issued 30 billion song identification requests, growing by 20 million each day. With such widespread access to large digital music collections, there is substantial interest in scalable models for music processing. Optimization concepts and methods thus play an important role in machine models of music engagement, music experience, music analysis, and music generation.

In this talk, we will show how optimization ideas and techniques have been integrated into computer models of music representation and expressivity, and into computational solutions to music generation and structure analysis. More specifically, we will report on research and outcomes on an interior-point approach to modeling tonal perception (inferring the keys and chords from note information), the idea of duality in reverse-engineering music structure analyses, constraint-based music generation to instill long-term structure, an optimization heuristic for stream segregation separating out voices from a polyphonic texture), statistical and optimization-based approaches to music segmentation, and rhythm transcription that minimizes quantization error for music and arrhythmia sequences. The talk will contain numerous music illustrations and, where appropriate, live performances of music and demonstrations of interactive visualization software on a piano or keyboard.

Elaine Chew
Professor at Queen Mary University of London

Elaine Chew is Professor of Digital Media in the School of Electronic Engineering and Computer Science at Queen Mary University of London, where she is affiliated with the Centre for Digital Music, since 2011. Prior to that, she was a tenured Associate Professor at the University of Southern California, where she held joint appointments in the Viterbi School of Engineering and the Thornton School of Music (courtesy). Her research centers on the mathematical modeling and and computational analysis of music structures, with recent applications to cardiac signal analysis. She is recipient of a Presidential Early Career Award for Scientists and Engineers in the US and the Edward, Frances, and Shirley B. Daniels Fellowship at the Radcliffe Institute for Advanced Study at Harvard. She is author of numerous research papers and a recent monograph on Mathematical and Computational Modeling of Tonality, the first volume on music in the Springer International Series on Operations Research and Management Science. Prof. Chew received PhD and SM degrees in Operations Research from MIT, a BAS in Mathematical and Computational Sciences (honors) and Music Performance (distinction) from Stanford, and Fellowship and Licentiate diplomas in piano performance from Trinity College, London.