IIT People Search

Address
Research center
Interests
About

I am a post-doctoral researcher in movement and computer science. My research focuses on the close connection between movement and music. In particular, I’m interested in spontaneous movements during music production and music listening. Currently, I’m investigating music-induced movements in interactive scenarios. Combining 3D motion capture and neuroimaging techniques, we aim to understand how specific movements are recruited during joint music activities and whether they may serve social communicative purposes.

Education

Title: PhD (Computer Science)
Institute: Paris Saclay University
Location: Orsay
Country: France
From: 2018 To: 2021

Title: Master (Engineering, Artificial Intelligence)
Institute: Sorbonne University
Location: Paris
Country: France
From: 2016 To: 2018

Title: Bachelor (Electronics and Automation)
Institute: Sorbonne University
Location: Paris
Country: France
From: 2015 To: 2016

Title: DEM: professional music degree in classical Percussions
Institute: Conservatoire Régional
Location: Dijon
Country: France
From: 2003 To: 2013

Experience External

Title: Research engineer (Miming musical instruments using motion capture for collective musical experience)
Institute: Burgundy University
Location: Dijon
Country: France
From: 2017 To: 2017

Title: Research engineer (Musical sonification of movements with motion capture and Max/MSP)
Institute: Burgundy University
Location: Dijon
Country: France
From: 2016 To: 2016

All Publications
2022
Bigand F., Prigent E., Braffort A.
Synthesis for the Kinematic Control of Identity in Sign Language
7th International Workshop on Sign Language Translation and Avatar Technology: The Junction of the Visual and the Textual
Conference Paper Conference
2022
Bigand F., Novembre G.
Watch my moves at the silent disco: effects of music and social visual cues on spontaneous movement and interpersonal synchrony
FENS Forum 2022
Poster Conference
2021
Bigand F., Prigent E., Berret B., Braffort A.
Decomposing spontaneous sign language into elementary movements: A principal component analysis-based approach
PLoS ONE, vol. 16, pp. e0259464
2021
Bigand F.
Extracting human characteristics from motion using machine learning: the case of identity in Sign Language
HAL Archive, Publisher: CNRS
PhD Thesis Book
2021
Bigand F., Prigent P., Berret B., Braffort A.
How Fast Is Sign Language? A Reevaluation of the Kinematic Bandwidth Using Motion Capture
29th European Signal Processing Conference, EUSIPCO 2021
Conference Paper Conference