My research started off with comparing the performance of automated algorithms against humans for cross-cultural music similarity. I worked on some analysis of diversity in Indian music and I'm currently working on the global jukebox project.

I mostly use R, Python and write my code in Jupyter Notebooks. I'm good at plotting data, cleaning data, performing dimensionality reduction, some basic DSP, and implementing simple machine learning models.

Related fields: Ethnomusicology, MIR, Music Perception, Evolution, Cross-cultural, Musicology.


  1. Daikoku, H., Ding, S., Sanne, U. S., Benetos, E., Wood, A. L., Fujii, S., & Savage, P. E. (2020). Human and automated judgements of musical similarity in a global sample.

  2. Shenghao, D., Daikoku, H., Sanne, U. S., Kinoshita, M., Konno, R., Kitayama, Y., ... & Savage, P. E. Late-Breaking/Demo.

Conferences, workshops and invited talks

  1. McMaster NeuroMusic Conference 2020

  2. ICTM 2019

  3. DMRN+14

  4. ISMIR 2018 Late-Breaking Demo

Awards, Honors and Scholarships

  • GAO Scholarship. 2020-2021
    Full tuition waiver given to top 3 graduate students.

  • Yamaha Full Ride Research Fund. 2020-2022.
    Research expenses, limited travel, stipend, and tuition.

  • University-wide Class Representative Graduate Class of 2020. 2020.
    Commencement speaker.

  • Young Scholar's Fund ICTM. 2019.
    Travel and accommodation to Bangkok given to top young scholars in Ethnomusicology.

  • Keio Shonan Fujisawa Academic Society Conference Travel Fund. 2018.
    Travel and accommodation to Paris for ISMIR 2018.