The ICube laboratory is structured into 4 departments, encompassing 17 research teams:
Their research spans both fundamental and applied approaches, addressing major scientific and technological challenges.
The team develops efficient geometric models that account for the diverse nature of data to design and reproduce the shape, appearance, and motion of 3D objects. These models enable accurate visualization, simulation, and interaction within virtual environments.
Computer graphics, geometric modeling, specification and proofs, rendering and visualization, simulation and interaction, virtual reality
The ICube Networksteam conducts cutting-edge research in computer networking, with expertise spanning from experimental systems to the design of distributed algorithms and network protocols.
Internet of Things (IoT), communication networks, network protocols, energy efficiency, fault tolerance, distributed algorithms, cellular networks, programmable networks
The team focuses on developing, adapting, and extending automatic and semi-automatic parallelization and optimization techniques, as well as proof and certification methods, to accelerate applications through the efficient use of current and future multiprocessor and multicore hardware platforms.
parallel computing, code optimization, compilation, static and dynamic analysis, code transformation, polyhedral modelling, verification
The SDC team develops fundamental methods in machine learning and knowledge modeling, while exploring their application to complex data from the environment, industry, the humanities, and healthcare.
machine learning, knowledge modeling and representation, data mining, deep learning, neuro-symbolic approaches, explainability, multimodal data, spatio-temporal data, remote sensing, digital histopathology, factory of the future, environment
The CSTB team conducts research in intelligent computing, including reasoning over complex data and AI (deep learning, natural language processing, and graph-based learning), with applications in healthcare, biodiversity, and industry.
artificial intelligence, optimization, graphs, algorithms, genomics, evolution, biodiversity, healthcare
The MLMS team develops models and methods that combine simulation, optimization, and learning to analyze and control complex systems and support computer-assisted medical interventions.
algorithmic optimization, numerical simulation, machine learning, geometric modeling, scientific computing, biological systems, biomechanical systems
Development of mathematical and algorithmic methods for modeling, analyzing, and processing signals, images, and data, with strong biomedical expertise and a focus on clinical applications.
discrete geometry, morphology, statistical learning, segmentation, medical imaging, diagnosis, Bayesian inference
The team designs and coordinates robotic systems and AI methods to assist surgical and medical procedures, integrate data and images, and control complex sparse systems.
medical robotics, interventional imaging, machine learning, biomechanical simulation, systems control, sparsity, AI for healthcare, computer-assisted surgery
The team extracts and analyzes physical information from optical signals to produce quantitative images, model cutural heritage sites and urban environments, and support studies in climatology, health, and food security.
spectro-polarimetric imaging, quantitative imaging, holography, augmented reality, 3D acquisition, photogrammetry, heritage digitization, urban modeling
The team combines multimodal imaging and metabolomics to identify and validate biomarkers, understand pathophysiology, and guide therapies in neuroscience and oncology.
quantitative MRI, spectroscopy, metabolomics, biomarkers, brain connectivity, neurosurgery, preclinical imaging, neuroscience, Alzheimer’s disease, Lewy body disease
The team synthesizes materials, characterizes and models their physicochemical properties, and integrates them into devices for energy conversion, sensing, and information technologies.
nanostructured materials, thin films, organic and inorganic semiconductors, computer-aided materials modeling, photovoltaic conversion physics, thermal properties at the nanoscale, solar cells, sensors, quantum sensors
Develops innovative electronic and multidomain systems and microsystems that address industrial challenges and emerging societal issues in healthcare, energy, and the environment.
microsystems, electronics, sensors, integrated circuits, modeling, CAD, system integration, multidomain systems, innovation, industrial applications
The IPP team conducts research in photonic instrumentation and processes, focusing on the interaction of light with complex media such as micro- and nanostructured materials and biological tissues, with the goal of extracting information or modifying their properties.
ultrashort laser processing, carbon electrodes, innovative optical components, metamaterials, microscopy, spectroscopy, OCT, optical elastography, Raman microscopy, fluorescence microscopy, hyperspectral imaging
The team studies and models fluid flows and their interactions across a variety of contexts. Research includes optimizing aircraft wing morphing, the melting of a spherical ice cube in a flow, particle behavior in turbulent flows, and two-phase heat exchangers. Applications extend to water management, hydraulic energy, and environmental protection, from rivers to urban systems.
urban flows, turbulence, reactive transfers, hydraulic energy, multiphase fluids, microfluidics, ecological engineering.
Studies the mechanics of biological tissues and biomaterials across multiple scales, develops biofidelic models, and designs intelligent processes to better understand mechanical behavior and its biomedical and industrial applications.
biomechanics, biomaterials, biological tissues, biofidelic modeling, multiscale mechanics, intelligent processes, dynamic simulation.
The GCE team conducts research on the interactions between civil structures and their environment, contributing to the development of sustainable cities through models and processes operating at multiple scales.
materials, structures, heat transfer, energy efficiency, renewable energy, sustainability, multiscale modeling, seismic engineering, environmental interactions
This team focuses on formalizing and advancing methods for product and system design, as well as conducting life cycle analysis, in the context of digital transformation within socio-technical organizations and Industry 5.0.
conception inventive, système d’information, systèmes sociotechniques, cycle de vie, transition numérique, analyse organisationnelle
