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Daniel Racoceanu
Professor @ Sorbonne University, Faculty of Science and Engineering, Paris, France
PI @ Paris Brain Institute (ICM), Inria team Aramis, Faculty of Medicine, Sorbonne University
68%
Open access
56
Documents
Current affiliations
- 542032
- 542029
- 413221
Researcher identifiers
daniel-racoceanu
-
0000-0002-9416-1803
- IdRef : 158147839
- Google Scholar : https://scholar.google.fr/citations?user=2eBRLj0AAAAJ
- ResearcherId : F-4576-2011
Presentation
**Biography**
Professor in BioMedical Image, Pattern Recognition, Machine / Deep Learning and Information / Data Analytics at Sorbonne University, and Principal Investigator at the Paris Brain Institute[\[1\]](#_ftn1) within the INRIA team “Aramis Lab”, my research is focusing on microscopic biomedical image analysis, pattern recognition (including machine & deep learning) and computational integrative pathology, by exploring novel explainable artificial intelligence mechanisms.
Dr.Habil./HDR (2006) and Ph.D. (1997) of the Univ. of Franche-Comté, Besançon, France, I was Project Manager at General Electric, before joining, in 1999, a chair of Associate Professor at University of Besançon & Research Fellow at FEMTO-ST Institute - UMR CNRS 6174.
From 2005 to 2014, I participated to the creation and the development of the International Joint Research Unit/Lab IPAL (UMI CNRS 2955) Singapore, being the Director (from 2008 to 2014) of this joint research venture created between Sorbonne University, the French National Center for Scientific Research (CNRS), the National University of Singapore (NUS) and the Agency for Science, Technology and Research (A\*STAR). From 2009 to 2015, I was Professor at the School of Computing, National University of Singapore.
From 2014 to 2016, I was a member of the Executive Board of the University Institute of Health Engineering of the Sorbonne University, being also co-Director of the Cancer Theranostics research team at the Bioimaging Lab (LIB - CNRS UMR 7371, Inserm U 1146).
From 2016 to 2018 I was Professor in BioMedical Image and Data Analytics at the Pontifical Catholic University of Peru.
Member of the European Society for Digital Integrative Pathology (ESDIP) Advisory Board since 2020, I was President (2018-2020) and Vice-President (2016-2018) of this European society.
From 2018 to 2022, I was member of MICCAI (Medical Image Computing & Computer Assisted Intervention) Board of Directors. Besides being the MICCAI 2020 general chair, I was also involved in the MICCAI 2021 and MICCAI 2022 organization committees.
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[**\[1\]**](#_ftnref1) Paris Brain Institute (Institut du Cerveau – ICM) - Stakeholders : Sorbonne University and French National Center for Scientific Research (CNRS UMR7225), French National Institute of Health and Medical Research - Inserm U1127 and AP-HP (Greater Paris University Hospitals) - UM75.
Skills
Computational Pathology
Explainable Artificial Intelligence
Medical image analysis
Biomedical image analysis
Deep Learning
Machine Learning
Computer Vision
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Reconstruction vasculaire 3D et analyse de lames virtuelles H&E dans l'étude du mélanomeIABM2023 : Colloque Français d'Intelligence Artificielle en Imagerie Biomédicale, Mar 2023, Paris, France
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Preliminary approach for crypt detection in Inflammatory Bowel DiseaseJournées RITS 2015, Mar 2015, Dourdan, France. pp.138-139
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Un explorateur visuel cognitif (MIcroscope COgnitif - MICO) pour l'histopathologie. Application au diagnostic et à la graduation du cancer du sein.RITS 2011, Recherche en Imagerie et Technologies pour la Santé, Apr 2011, Rennes, France. pp.119
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Spatial Relationships over Sparse RepresentationsSpatial Relationships over Sparse Representations, IVCNZ 2009 - Image and Vision Computing, Nov 2010, Wellington, New Zealand
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Knowledge-Guided Semantic Indexing of Breast Cancer Histopathology ImagesBMEI2008, International Conference on BioMedical Engineering and Informatics, May 2008, Sanya, Hainan, China
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A fuzzy approach for discrete event systems recovery.IFAC - International Federation of Automatic Control. 4th IFAC Conference on Management and Control of Production and Logistics, MCPL'2007., Sep 2007, Sibiu, Romania. pp.585-590
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IPAL Knowledge-based Medical Image Retrieval in ImageCLEFmed 2006Working Notes for the CLEF 2006 Workshop, 20-22 September Medical Image Track, 2006, Alicante, Spain
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From the spherical to an elliptic form of the dynamic RBF neural network influence field2002 International Joint Conference on Neural Networks (IJCNN), May 2002, Honolulu, United States. pp.107-112, ⟨10.1109/IJCNN.2002.1005452⟩
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A Petri nets graphic method of reduction using birth-death processes2001 ICRA. IEEE International Conference on Robotics and Automation, May 2001, Seoul, South Korea. pp.46-51, ⟨10.1109/ROBOT.2001.932528⟩
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Responsible artificial intelligence : a review of current trendsConference poster hal-03834390v1 |
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Resource-Centered Distributed Processing of Large Histopathology Images19th IEEE International Conference on Computational Science and Engineering, Jun 2016, Paris, France. 2016
Conference poster
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Computational Pathology for Brain DisordersO. Colliot (Ed.). Machine Learning for Brain Disorders, 197, Springer; Humana, New York, NY, pp.533-572, 2023, Part of the Neuromethods book series (NM,volume 197), 978-1-0716-3195-9. ⟨10.1007/978-1-0716-3195-9_18⟩
Book sections
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Innovative Deep Learning Approach for Biomedical Data Instantiation and VisualizationMourad Elloumi. Deep Learning for Biomedical Data Analysis. Techniques, Approaches, and Applications, Springer International Publishing, pp.171-196, 2021, 978-3-030-71675-2. ⟨10.1007/978-3-030-71676-9_8⟩
Book sections
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Phagocytosis Unveiled: A Scalable and Interpretable Deep learning Framework for Neurodegenerative Disease Analysis2023
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Prospective Study for Semantic Inter-Media Fusion in Content-Based Medical Image Retrieval2008
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Contribution à la Surveillance des Systèmes de Production en Utilisant l'Intelligence ArtificielleAutomatique / Robotique. Université de Franche-Comté, 2006
Habilitation à diriger des recherches
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