Senior Lecturer in Acoustics

Accredited to Supervise Research

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Éric Bavu

Senior Lecturer (HDR)

LMSSC

Cnam Paris

I am a lecturer at Cnam Paris since September 2009, in the acoustics team of the Laboratoire de Mécanique des Structures et des Systèmes Couplés .

To date, I have officially co-supervised PhD students (4 defended, 2 in progress since December 2021), and I am leading since early 2019 the ANR Deeplomatics until June 2022.

I defended my accreditation to supervise research (HDR) in December 2019. My habilitation thesis has been deposited on HAL , and I leave available a chaptered video of the defense as well as the slides in html.

My research activities are focused on inverse problems in acoustics, signal processing associated with microphonic arrays, and Deep Learning methods for acoustics.

Interests

  • Inverse problems in time domain
  • Deep Learning applied to acoustics
  • Source localization
  • Reverberant and noisy environments
  • 3D Audio
  • Transient elastography (post-doc)

Education

  • Accreditation to Supervise Research, Acoustics, 2019

    Conservatoire National des Arts et Métiers (FR)

  • PhD thesis in Mechanical Engineering, Acoustics Specialty, 2008

    Cotutelle University of Sherbrooke (Qc, CA) and University Paris 6 Pierre et Marie Curie (FR)

  • Master in Acoustics, Signal Processing and Computer Science (ATIAM), 2005

    Pierre et Marie Curie University (FR)

  • Teacher training degree (french Agregation) Physics, 2004

    École Normale Supérieure de Cachan (FR)

  • Bachelor and Master of Fundamental Physics, 2002-2003

    École Normale Supérieure de Cachan / Université d'Orsay (FR)

Recent and upcoming talks

Deeplomatics - A deep-learning based multimodal approach for aerial drone detection and localization

Realtime Identification and geolocalization of flying drones.

Deep Learning enhancement of speech signals captured with in-ear transducers

Improving speech intelligibility recorded by in-the-ear transducers

Recent publications

(2022). Deeplomatics project: Multimodal UAV detection, localisation and identification for site surveillance. 8th Workshop on Battelfield Acoustics, ISL.

PDF

(2022). 3D acoustic source localization using Deep Learning : training procedure using a higher order ambisonic spatialization process.. CFA2022 - 16E CONGRÈS FRANÇAIS D’ACOUSTIQUE DE LA SFA.

PDF Project Project

(2022). Deep Learning enhancement of speech captured with in-ear transducers. CFA2022 - 16E CONGRÈS FRANÇAIS D’ACOUSTIQUE DE LA SFA.

PDF Project Talk

(2022). Deeplomatics: Acoustic Localization and recognition of drones. CFA2022 - 16E CONGRÈS FRANÇAIS D’ACOUSTIQUE DE LA SFA.

PDF Project

Experience

 
 
 
 
 

Senior Lecturer (HDR)

Laboratoire de Mécanique des Structures et des Systèmes Couplés

Sep 2009 – Present Cnam Paris

Research activities focused on microphonic array signal processing, inverse problems in the time domaine in acoustics, deconfinement, moving source localization, and the use of Deep Learning in acoustics for source localization and sound source recognition.

  • Accredited to supervise research (HDR) since 2019
  • 6 PhD students co-supervised since 2011
  • 1 post-doctorate fellow supervised (2020-2022)
  • Participation in 6 research projects since 2008 (3 ANR, 2 of which are ongoing, 2 FUI, 1 regional project)
  • Project leader and coordinator of an ANR ASTRID project (Deeplomatics 2019-2022)

Courses in acoustics and signal processing for initial training, apprenticeship diplomas, and Cnam engineering courses in evening classes, in-class and distance learning. Students from Bac+1 to Bac+5.

 
 
 
 
 

Post-doc CNRS

Institut Langevin, Équipe Physique des Ondes pour la Médecine

Dec 2008 – Aug 2009 ESPCI Paris
Transient and broadband elastography by ultrasound imaging method Supersonic Shear Imaging for the detection of liver fibrosis
 
 
 
 
 

PhD thesis

Institut Jean le Rond d’Alembert / Groupe d’Acoustique de l’Université de Sherbrooke

Sep 2005 – Oct 2008 Paris / Sherbrooke
High resolution focusing and imaging using time reversal in the audible domain. Development a digital time-reversal sink for imaging, with applications to localization and characterization of unsteady acoustic sources.

Research Projects

Ongoing contracts and supervised PhDs

*

Bandwidth extension of speech signals

Julien Hauret’s PhD thesis (2021- 2024)

Sound recognition using Deep Learning

TimeScaleNet, a multi-resolution time domain architecture for speech and environmental sound recognition

ANR ASTRID project ‘Deeplomatics’

Project leader - DGA funding 2019-2022

Acoustic sources in supersonic motion

Guillaume Mahenc’s PhD thesis (2014-2017)

Contact

  • +33 1 40 27 21 66
  • Cnam, 2, rue Conté, Paris, 75003
  • Laboratoire de Mécanique des Structures et des Systèmes Couplés, Accès 31, Bureau 31.0E.02