Dorien Herremans

Assistant Professor

Email: qbevra_ureerznaf@fhgq.rqh.ft
Website: dorienherremans.com
Telephone: +65 6499 7155
Room Number: 1.202.17
Research Interests:
Multi-Modal Information Retrieval,Machine Learning and Artificial Intelligence,Audio Analysis,Multimedia,Database and Big Data Analytics

Pillar / Cluster: Information Systems Technology and Design

Biography

Dr. Dorien Herremans received her PhD in Applied Economics from the University of Antwerp. Her PhD thesis was titled ‘Computer Generation and Classification of Music through Operations Research Methods’. She was awarded the individual Marie-Curie Fellowship for experienced researchers in 2015. This allowed her to join the Centre for Digital Music at Queen Mary University of London, where she worked on the project: “MorpheuS: Hybrid Machine Learning – Optimization techniques To Generate Structured Music Through Morphing And Fusion”. After graduating as a commercial engineer in management information systems at the University of Antwerp in 2005, she worked as a Drupal consultant and was an IT lecturer at the Les Roches University in Bluche, Switzerland. She also worked as a mandaatassistent at the University of Antwerp, in the domain of operations management, supply chain management and operations research, and was a visiting researcher at the Department of Computer Science and Artificial Intelligence at the University of the Basque Country, San Sebastián. She is currently and Assistant Professor at Singapore University of Technology and Design and has a joint appointment at the Institute for High Performance Computing at the Agency for Science, Technology and Research (A*STAR).

Dr. Herremans’ research has been featured in popular press including Vice Magazine, Belgian national TV news and France Info radio. Her research interests include machine learning and music for automatic music generation, data mining for music classification (hit prediction) and novel applications in the intersections of machine learning/optimization and domains such as digital music and stock market prediction.

Education Experience

  • PhD, Applied Economics, University of Antwerp, Belgium
  • MSc, Commercial Engineering MIS, University of Antwerp, Belgium

Awards

  • Individual Marie Sklodowska-Curie Fellowship for Experienced Researchers, EU Research Council. Host institution: Queen Mary University of London, UK.

Selected Publications

For a full list of publications, please see here.

  • Herremans D., Chuan C.-H., Chew E..  In Press.  A Functional Taxonomy of Music Generation Systems. ACM Computing Surveys
  • Herremans D., Chew E..  In Press.  MorpheuS: generating structured music with constrained patterns and tension. IEEE Transactions on Affective Computing.
  • Agres K., Herremans D., Bigo L., Conklin D..  2017.  Harmonic Structure Predicts the Enjoyment of Uplifting Trance Music. Frontiers in Psychology, Cognitive Science. 7(1999). Link
  • Herremans D., Chuan C.-H..  2017.  Modeling Musical Context with Word2vec. First International Workshop On Deep Learning and Music joint with IJCNN. Anchorage, US, 1:11-18. Link
  • Herremans D., Chuan C.-H..  2017.  A multi-modal platform for semantic music analysis: visualizing audio- and score-based tension. 11th International Conference on Semantic Computing IEEE (ICSC 2017). San Diego, US. Link
  • Balliauw M., Herremans D., D. Cuervo P, Sörensen K..  2017.  A variable neighborhood search algorithm to generate piano fingerings for polyphonic sheet music. International Transactions in Operational Research, Special Issue on Variable Neighbourhood Search. 24(3):509–535. Link
  • Herremans D., Sörensen K., Martens D.  2015.  Classification and generation of composer-specific music using global feature models and variable neighborhood search. Computer Music Journal. 39(3):91. Link
  • Herremans D., Weisser S., Sörensen K., Conklin D..  2015.  Generating structured music for bagana using quality metrics based on Markov models. Expert Systems With Applications. 42 (21)(21):424–7435. Link
  • Herremans D., Martens D, Sörensen K..  2014.  Dance hit song prediction. Journal of New music Research. Special Issue on Music and Machine Learning. 43:302. Link
  • Herremans D., Sörensen K..  2013.  Composing Fifth Species Counterpoint Music With A Variable Neighborhood Search Algorithm. Expert Systems with Applications. 40.16 (2013): 6427-6437. Link
  • Herremans D., Sörensen K..  2013.  FuX, an Android app that generates counterpoint. IEEE Symposium on Computational Intelligence for Creativity and Affective Computing (CICAC). :48-55. Link