Olivier Galeran

Olivier Galeran
Name	Olivier Galeran
Birth date	1970s
Birth place	Paris, France
Fields	Signal processing; Machine learning; Audio engineering
Institutions	CNRS; École Normale Supérieure; Inria; Télécom Paris
Alma mater	Université Pierre et Marie Curie; École Normale Supérieure
Known for	Speech separation; Source localization; Blind source separation

Olivier Galeran is a French researcher and engineer known for work in signal processing, machine learning, and audio engineering, particularly in the areas of speech separation and source localization. He has held positions at major French research institutions and contributed to applied and theoretical advances that intersect with industry technologies used in telecommunications and multimedia. Galeran's career spans academia, national research laboratories, and collaborative projects with industrial partners.

Early life and education

Galeran was born in Paris and completed early studies at institutions including Lycée Louis-le-Grand and Université Pierre et Marie Curie where he studied electrical engineering and applied mathematics. He pursued graduate research at the École Normale Supérieure and obtained advanced degrees that combined rigorous training in signal processing methods with applied studies relevant to speech and audio. During this formative period he interacted with research groups associated with CNRS, Inria, and technical laboratories linked to Thales Group and Orange S.A., which influenced his later specialization.

Academic and research career

Galeran's early appointments included positions at research units of CNRS and lab affiliations within Télécom Paris and ENSTA ParisTech. He collaborated on projects funded by European frameworks such as Horizon 2020 and national programs administered by ANR (Agence nationale de la recherche). Throughout his career he has worked alongside researchers from institutions like Massachusetts Institute of Technology, Imperial College London, École Polytechnique, and University of Cambridge on interdisciplinary teams addressing challenges in blind source separation, microphone array processing, and robust speech enhancement. He has supervised doctoral candidates who later joined organizations such as Google Research, Facebook AI Research, Apple, and Microsoft Research.

Galeran contributed to international conferences including the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP, Interspeech, and NeurIPS, and served on program committees for venues like ICASSP and EUSIPCO. He has participated in collaborative consortia with industrial partners such as Nokia, Ericsson, Dolby Laboratories, and participated in standards-related activities involving 3GPP and MPEG communities.

Major contributions and publications

Galeran's research portfolio includes pioneering work on blind source separation techniques that extend classical approaches like Independent Component Analysis and Nonnegative Matrix Factorization to multi-microphone and reverberant environments. He published methods combining spatial covariance modeling with deep learning, integrating architectures inspired by convolutional neural networks and recurrent neural networks applied to audio. His work addressed practical problems relevant to hearing aids, teleconferencing, and automatic speech recognition systems developed by groups at IBM Research and Nuance Communications.

Notable publications appeared in journals such as IEEE Transactions on Audio, Speech, and Language Processing, IEEE Signal Processing Letters, and proceedings of ICASSP and Interspeech. Selected contributions include advances in sparse representation for source localization related to MUSIC algorithm extensions, neural beamforming approaches that relate to work by teams at University of Southern California and Johns Hopkins University, and algorithms for dereverberation that built upon concepts from Wiener filter theory. Galeran also co-authored survey chapters and tutorials that synthesize results from groups at CMU, Stanford University, and ETH Zurich.

His collaborative publications often cite and extend methods from researchers such as Jean-François Cardoso, Simon Haykin, Herve Glotin, and groups working on computational auditory scene analysis including researchers at University of York and KTH Royal Institute of Technology.

Awards and honors

Galeran received recognition from national and international bodies including awards and grants from CNRS programs and competitive funding from ANR (Agence nationale de la recherche). He was principal investigator or co-PI on EU-funded projects supported by Horizon 2020 and received best paper nominations at conferences such as ICASSP and Interspeech. Institutional honors included internal distinctions at Télécom Paris and invited lectureships at universities including EPFL and University of Illinois Urbana-Champaign.

Personal life and affiliations

Outside his research, Galeran has been active in professional societies such as the Institute of Electrical and Electronics Engineers (IEEE) and the International Speech Communication Association (ISCA). He participated in outreach initiatives connected to science festivals and industrial consortiums involving Thales Group and Dassault Systèmes. He has collaborated with startup ventures in audio technology and is affiliated with research networks that include Inria teams and academic centers such as Laboratoire d'Informatique de Paris 6.

Category:French scientists Category:Signal processing researchers Category:1970s births