Research Interests

Digital signal processing, data mining and machine learning in the context of  music information retrieval, sound and music computing and machine listening.
​
Specific research interests:
Within music information retrieval (MIR) I focus on audio content processing for extraction of musically meaningful metadata from polyphonic recordings. During my PhD within CompMusic project I am working towards developing culturally informed computational models for melodic description of Indian art music. Main topics during my PhD research includes:

1. ​Computational models for melodic similarity in the context of characteristic rāga phrases in Indian art music.
2. Large scale unsupervised discovery of melodic patterns in audio recordings.
3. Modeling abstract concepts such as Rāga in Indian art music using melodic patterns and other melodic characteristics.

Teaching and Scientific Service

​Audio Signal Processing for Music Applications (ASPMA), MOOC-Coursera: 

• Teaching assistant for MOOC course ASPMA offered through Coursera for two consecutive years 2014-2015. 
• Contributed to design and implementation  programming assignments and automated graders.

Processament de So i Música, Universitat Pompeu Fabra, Barcelona, Spain

• Teaching assistant for undergraduate course in UPF for three consecutive years 2013-2015. 
• #Seminars, #Labs, #Programming assignments, #Automatic graders

Reviewer:

• The International Society of Music Information Retrieval (ISMIR), for the last 5 years (2013-2018)
• National Conference on Communications (NCC), #2015
• Journal of Intelligent Information Systems (JIIS), #2016
• Journal of New Music research (JNMR), #2016
• IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP), #2016, #2017
• IEEE Transactions on Multimedia, #2017
• EURASIP Journal on Audio, Speech, and Music Processing,  #2018
• ETE Technical Review Journal, #2018
• IEEE Journal of Selected Topics in Signal Processing, #2018
• Speech Music and Mind (SMM), #2018