Workshops

W1: Recent developments in multiblock methods and the use of the RGCCA package, by Pr. Arthur Tenenhaus

You can submit workshop proposals until April 17, 2026.

Invited speakers

Heterogeneous data integration and fusion

Pr. Arthur Tenenhaus. Arthur Tenenhaus is professor of statistics/machine learning at CentraleSupelec (top engineering school in France) and member of the  ‘Signals and Statistics’ group of the Laboratoire des Signaux and Systèmes. He is also researcher affiliated to the Paris Brain Institute (ICM) at La Pitié-Salpêtrière Hospital and co-holder of the chair  APHP-CentraleSupelec- INRIA. His main research interest concerns the development of statistical framework for  the joint analysis of heterogeneous and complex data. This framework is usually motivated by applications  in molecular biology and neuroimaging.

Title: Structural equation modeling with factors and composites within the framework of the basic design

Summary: We study structural equation modeling with factors and composites in the framework of the basic design.  We propose two estimation methods. The first one is a new non-iterative approach based on singular  value decomposition calculations (SVD-SEM). This new approach produces consistent and asymptotically  normal estimators of the parameters. Then, we describe the restricted maximum likelihood approach in  the framework of the basic design. We evaluate the efficiency and usefulness  of SVD-SEM and ML-SEM  in a Monte Carlo simulation and on a case study.

Modeling and digital twins

Dr. David Camilo Corrales. David Camilo Corrales is a computer scientist with a PhD in Computer Science specialized in Artificial Intelligence from Universidad Carlos III de Madrid (Spain). He has completed three postdoctoral fellowships at INRAE Occitanie-Toulouse, where he developed machine learning models for pest, disease, and weed prediction in agronomic applications. He holds a bachelor’s degree in software engineering and a master’s degree in telematics engineering from Universidad del Cauca (Colombia). His applied research in AI spans different domains, including water quality, volcanology, and agronomy. Since 2021, he has focused on digital and cyber-physical systems in biotechnology. He has authored more than fifty publications in peer-reviewed journals and international conferences. Currently, he works at INRAE - Toulouse Biotechnology Institute (TBI), where he contributes to the development of digital twins, virtual sensors (soft sensors), and hybrid models integrating machine learning with dynamic process modeling. His expertise in MLOps pipelines for real-time deployment of AI-based solutions supports the creation of scalable, robust, and data-driven digital systems for complex cyber-physical infrastructures.

Title: Digital Twins and Industry 4.0: From Physical Models to Operational Intelligence with AI and MLOps

Abstract: The convergence of digital technologies with industrial biotechnology is transforming how modern bio-processes are designed, optimized, and operated. As the sector moves toward the vision of Industry 4.0, new approaches are required to accelerate research and development, reduce time-to-market, and enable autonomous, adaptive, and sustainable production systems. This keynote will explore how digital twins, AI-driven operational intelligence, and MLOps pipelines are reshaping bio-process engineering from early-stage design to real-time control. Drawing on insights from the European initiative BIOINDUSTRY 4.0, the presentation will show how data centric and hybrid modeling strategies combine physical models with machine learning to create scalable digital infrastructures. We will discuss how advanced data standards and interoperable metadata frameworks contribute to high-quality multi-scale datasets, the foundation for digital twins. These digital twins, together with virtual sensors and hybrid models deployed in real time, enable predictive control and accelerate optimization in bioprocess development.

Behavioral & physiological analysis in context

Dr. Catherine Soladié, IETR

Visual data processing & automated image-based analysis

Dr. Rémy Sun, INRIA

Data quality, reliability and reproducibility

Pr. Anne-Laure Boulesteix, Department of Medical Informatics, Biometry and Epidemiology of the Faculty of Medicine, LMU Munich

Scientific program

The details of the scientific program will be communicated later. The agenda below is provisional.

Monday 5^th October

 Tuesday 6^th October

Wednedsay 7^th October