Call for Papers:
Explainable Artificial Intelligence for Critical Healthcare Applications. Frontiers in Artificial Intelligence (Deadline: May 19, 2022)
Recent years have seen an increase in the availability of digital data as never before. This is thanks to the development of new information communication and technologies (ICT) and medias from Web technologies : we have entered the era of Big Data for some time now. The situation is particularly noticeable in the health and life sciences sector. Electronic Health Records (EHRs), medical literature, social networks (twitter, web forums, etc.) and many other not health data per-se (e.g. Call Detail Records (CDRs)) are key drivers of enabling a digital health.
My research work attempts to leverage and integrate, in a multidisciplinary context, these type of data and knowledge at large scale for tackling issues in the healthcare domain. The designed and implemented methods are based on the elicitation (through knowledge formalization) and exploitation of semantics encoded in KOS. More specifically, I address the challenges posed in this context through the following research topics, some identified as sub-fields of Artificial Intelligence (AI) :
Knowledge Engineering in the Healthcare domain and Large Scale Ontology Matching;
Large Scale Biomedical Text Mining and Semantic Information Retrieval ; and
ICT for Development (ICT4D) as digital Public Health enabler, mainly in the context of Low and Middle Income Countries (LMIC).
AMALGAM: A Matching Approach to fairfy tabuLar data with knowledGe grAph Model [gitub]
OREGANO: Computational Approaches for Drug Repositioning: Towards a Holistic Perspective based on Knowledge Graphs [gitub]
K-Ware: Agnostic management of heterogeneous knowledge resources [gitub]
kANNA: Knowledge graph completion using Artificial Neural Networks. Funding: Georgeta Bordea postdoc Individual Fellowship (IF) project under H2020 Marie Skłodowska-Curie Actions and is hosted by the University of Bordeaux and the University of Oslo
INTENDED (2020-2024): Intelligent handling of imperfect information, Chaire IA Meghyn Bienvenu, collaboration on WP 3, application on health with a funded PhD thesis. Funding: ANR & University of Bordeaux
PATIENT-Covid19: Pre-diagnosis and follow-up of Covid-19 contacts. The aim is at contributing to the fight against FakeNews about the Coronavirus, to reduce the flow of people requesting tests at Covid-19 testing centers and the follow-up of contacts by providing a multilingual information platform available on the internet and on cell phones, accessible in the local languages most spoken in the project's target countries (French, Wolof, Peul, Moré, Fan, Malinké, Dioula). The project addresses the West African countries, Cameroon and Gabon.
EHVA (European HIV Vaccine Alliance, H2020) : 2016-2020. INSERM 1219 (Pr Rodolphe Thibeaut) leads Work Package Data Integration and Down Selection of Vaccine Candidates under scientific coordination of Rodolphe Thiebaut (SISTM team of BPH INSERM 1219)
e-ATM: eEnhancing Patient Safety In African Traditional Medicine. Period: 2016-2017. funding: ANR MRSEI. Status: Scientific coordinator.
DIMMER: Détection de Mésusages de Médicaments à partir de réseaux sociaux et forums. Period: 2016-2017. Funding: PEPS IDEX Bordeaux, Budget 16KEuros, Status: Scientific coordinator
Prizes and Awards
2020: French sabbatical leave award, Congé de Recherches et Conversion Thématiques (CRCT), 6 months leave
2003 - present: Scientific Excellence Bonus (PEDR), French Ministry of Higher Education and Research
2015: Practical Application Prize Winner of the Data for Development Big Data International Challenge, Orange-Sonatel – MIT, USA.
2015: Winner of the Finland-France research fellowships SAMPO program, edition 2015, French Institute in Finland
2012, 2013 and 2015: the ServOMap large scale Ontology Matching system ranked among Top 3 best systems during the Ontology Alignment Evaluation Initiative (OAEI), large biomed track. The KEPLER system ranked best multilingual Ontology Alignment tool (OAEI 2017 and 2018)