SDC, Data Science and Knowledge

Projects

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Current projects

  • AIGE FOR BANK (2020-2021) : Artificial intelligence, governance and ethics - Funding: CNRS / Enjeux scientifiques et sociaux de l’intelligence artificielle
  • Mi:EDGE (2020-2023): Modelling cell plasticity at the invasive Edge to Diminish Glioblastoma Early relapse risk in collaboration with Medical School of Hannover (Germany), Istituto Humanitas (Italy), Luxembourg Centre of Neuropathology (Luxembourg) and IRIMAS (France) - Funding: ERACoSysmed/ANR
  • ARISE (2020-2021): Artificial intelligence in the science system - Funding: CNRS / Enjeux scientifiques et sociaux de l’intelligence artificielle
  • POPLAB (2020-2021) : Innovative framework for education - Funding: AMI Economie numérique - Région Grand-Est
  • AiCOLO (2019-2022): Artificial intelligence to determine prognosis and mutation status in colorectal cancer using histological slides in collaboration with CGFL Dijon and IRIMAS - Funding: INSERM-Plan Cancer
  • Pancréas CGE (2019-2020): Multiparametric analysis of pancreatic ductal adenocarcinoma in collaboration with Pathology dpt (HUS) and Cancéropôle Est - Funding: Région Grand-Est
  • HIATUS (2019-2023) : Historical Image Analysis for Territory evolUtion Stories (PRCE) in collaboration with LaSTIG, LETG, DYNAFOR, LIVE and Kermap
  • ADQeau (2019-2020) : Analyse de la dynamique temporelle de la qualité physico-chimique et biologique des cours d’eau in collaboration with LIVE - Funding: Conseil scientifique ENGESS
  • HALFBACK (2017-2020) : Highly available smart factories in the cloud. Funded in the framework of the INTERREG V Upper Rhine program, through the Offensive Sciences call for projects of the Tri-National Metropolitan Region of the Upper Rhine. Partners: Hochschule Furtwangen, INSA Strasbourg, University of Strasbourg.

Local projects

  • ACE_game (2018-2019) : Anomaly detection by intelligent agents
  • METEC-Graphe (2019-2020): Modeling of spatial and temporal data for the extraction of knowledge via the use of graphs

Past projects

  • DA_HPC_OR (2018-2019) : EUCOR Seed Money - Data Analysis for High Performance Computing : Operation and Research
  • SysMIFTA (2016-2019): ERACoSysMed - Systems medicine approach to minimize macrophage-associated interstitial fibrosis and tubular atrophy in renal allograft rejection
  • Sysimit (2013-2019): BMBF - Systems Immunology and Image Mining in Translational Tissue Biomarker Research: Mining the spatial patterns of adaptive immune responses to persisting tissue antigens to exploit the full predictive potential of protocol biopsies in transplantation and cancer research
  • SEMNET (Sensor Networks for Smart Factories) - API ICube (2017-2018): this projet is an internal collaboration with the Network research team. Its objective is to analyze experimental data collected from the IoT-Lab (Internet of Things platform of the Network team), by applying data mining and machine learning techniques, in order to better understand the behaviour of the sensor network, and to propose algorithms for the diagnosis of network failure.
  • NEUROTEX - API ICube (2017-2018): this project is an internal collaboration with the IGG research team. Convolutional neural networks for texture synthesis.
  • Exploratory analysis of muddy flood representations in Alsace: extracting and formalizing graphical information (2016-2017). ENGEES conseil scientifique.
  • FOURIRE (Fuzzy Ontologies for URban Image REcognition) - API ICube (2014-2016): this projet is an internal collaboration with the MIV research team. Its goal is to take into account uncertainty through the whole process of semi-automatic recognition of urban objects from satellite Very High Resolution images.
  • Coclico (2012-2016): ANR MN - COllaboration, CLassification, Incrémentalité et COnnaissances
  • Reframe project (2012-2016): CHIST-ERA - Rethinking the Essence, Flexibility and Reusability of Advanced Model Exploitation
  • DAWSHI (2014-2015): ICube internal project - Deep Analysis of Whole Slide Histopathological Images
  • Fresqueau (2011-2015): ANR 11 MONU 14 - "Data mining for assessing and monitoring the hydrobiologic quality of running waters"