Singa is offering fellowships for International PhD students in Singapore. If you are interested in working in the AMAAI lab, send me a message. I am interested in supervising PhD students interested in the domain of Music Information Retrieval or AI for multimedia or finance.

More details on the application: https://www.a-star.edu.sg/Scholarships/for-graduate-studies/singapore-in...

Deadline for applications: January 1st!

Abigail Leon has successfully defended her PhD today with main supervisor Prof. Yuen Chau and myself as co-supervisor. Abigail has successfully explored how deep learning techniques can be used to denoise en demodulate complex underwater acoustic communication signals, and has performed some sea-trials to gather data for this. Since the PhD is under an NDA with Thales, we cannot post it, however, check out some of Abigail's papers here (more to come after the review process ends).

Big congrats to Quang-Hieu PHAM, my PhD student who successfully defended his PhD on "Data-driven 3D Scene Understanding", co-supervised by Prof. Gemma Roig and Prof. Sai-Kit Yeung.

I'm very happy to announce that Natalie Angus will be doing her PhD defence on Real-Time Binaural Auralization on August 1st. Natalie is supervised by myself and Dr. Simon Lui (Director of Tencent Music). Download and read her thesis here. Some information about the seminar:

Title: Real-Time Binaural Auralization

When: 15:00, August 1st, 2018.

Where: Think Thank 20 (Building 2, Level 3), SUTD

In 2014 I defended my PhD thesis, Compose=Compute - Computer Generation And Classification Of Music Through Operations Research Methods, at the Unviversity of Antwerp under the supervision of Prof. dr. Kenneth Sörensen. In the research, I have developed automatic music generation systems using metaheuristic optimization techniques, combined with rules and machine learning. Other topics included composer classification, and Android app that generates music in the style of a chosen (or mixed) composer's style, and an app that does dance hit prediction based on an audio file.