Alexandre BENOIT

Professor, Polytech Annecy-Chambéry.

Contact.

Email : alexandre.benoit –@– univ-smb.fr

Phone : +33(0) 4 50 09 65 22 – télécopie : +33(0) 4 50 09 65 22

Office :  A223

Postal address : LISTIC – Polytech Annecy Chambéry, BP 80439, 74944 Annecy le Vieux Cedex, France

Position / responsabilities.

• Permanent LISTIC Lab. member, professor position
• Main teaching activities at Polytech Annecy Chambéry, Université Savoie Mont Blanc.

Research interests.

    Member of the « Apprentissage, Fusion et Télédétection (AFuTé) thematic » with strong connexions with ReGaRD thematics on distributed systems, HPC, data and ethics,

• Image, video and more generally data understanding : from data preprocessing, features extraction to concept recognition (objects, action, etc.)  to classical 1D sensors.
• Heterogeneous Data Fusion : associating multimodal inputs, images, contextual indicators, and others to make the decision process more reliable.
• Sensor time series in general, from image sequences (multimedia, satellite remote sensing, astrophysics imaging) to classical sensors analysis.
• Current methodological approaches rely on deep learning methods with some specific directions:
  • Frugal models, low computational cost by design: light architectures efficient in terms of training efficacy as well as reduced inference time.
  • Explainable models, with two approaches:
    • physical aware models design : by introducing physical knowledge in the model structure or by introducing optimization criteria related to the physical phenomenon to be considered.
    • developing XAI visualization techniques to help explain and understand model behaviors and predictions.
  • Physically informed models, ongoing activity
  • Federated learning, distributed and privacy preserving machine learning, ongoing activity.

Keywords

Video clustering Classification Retina modelDeep Learning Semi-supervised learning 3D convolutional neural network V1 cortex model Semantic Segmentation Real-time retina Human vision Remote sensingSpectral Clustering 2D metrics 3DOpenInterface Deep learning Attention level, Pairwise constraints Graph Cut

Publications

An overview of my publications is provided here : https://cv.archives-ouvertes.fr/alexandre-benoit  and here also (subject to bugs) : registered in HAL

My Google Scholar report.

Research Projects

• A brief overview on these slides
• Current projects:
  • Gamma rays classification and parameters estimation.
    • Keywords : deep learning, astrophysics, model inversion, physics inspired models, domain adaptation, multitask learning, classification, regression.
    • Academic partner: LAPP
    • Industrial partner : Orobix
  • Federated Learning and bias mitigation
    • Keywords : deep learning, decentralized learning, model and data bias detection, clients clustering
    • Academic and industrial research
  • Deep learning for Alpin glacier model inversion
    • Keywords : deep learning, model inversion, physics inspired models
  • IoT and AI for health care
    • Keywords : deep learning, time series analysis
    • internal long run project at LISTIC
• Recent projects:
  • Oil slicks detection and classification.
    • Keywords : deep learning, SAR data analysis, heterogeneous data fusion, anomaly detection, semantic segmentation, classification.
    • Industrial partner : Total
  • Object detection and recognition for office inventory.
    • Keywords : deep learning, 360° images, 3D scene modelling.
    • Industrial partner : SmarterPlan.io

Teaching :

• Related to my research activities:
  • Image and data processing with tools such as Matlab, and Python, OpenCV
  • Deep larning with Tensorflow.
  • Target students : PhD, Master and Bachelor degree and employed engineers.
• General teaching activities:
  • Programming : scripting and object programming with C/C++/Java/Python/PHP, and others.
  • Modeling (UML, etc.)
• Experience highlights :
  • image processing and machine learning to PhD students and Master 2 at University Savoie Mont Blanc.
  • machine learning at ESEN engineering school at Tunis (Tunisia)
  • machine learning at Renault compagny (Paris, Versailles)

Consulting :

• Introducing machine learning in digital processes in the industry.
• Data pre-processing, features extraction and decision making for classification, regression and other tasks for image, video and time series understanding.
• Experience highlights :
  • Machine Learning and Deep Learning at Renault (Paris, Versailles)
  • Deep Learning at Total company(Paris)
  • Machine Learning at AboutGoods Company and Inventhys (Annecy)
  • Machine Learning with startups (Heliocity, Skiply and so on) along implications into the IDEFICS project

Personal pages.

Please click here.