DeepHealth External Advisory Board

DeepHealth has set up an independent External Advisory Board (ExtAB) formed by a panel of independent experts selected by DeepHealth partners to cover key areas of the project. The mission of the ExtAB is to provide comments and recommendations regarding requirements, objectives, and development, as well as exploitation and dissemination activities, in order to ensure the maximum impact of the DeepHealth project and the future exploitation of the project results.

Aurelia Bustos , Co-founder in Medbravo –

Aurelia Bustos, MD, PhD. is board-certified medical oncologist practicing during more than 18 years and computer science engineer with a PhD in AI applied to medical text and medical image. She has a multidisciplinary expertise in artificial intelligence, natural language processing, software engineering, health technology, clinical oncology, clinical trials and cancer research industry. She has participated in different e-Health projects promoted by European organizations and leading Spanish research institutions.

Her areas of expertise cover the following: application of AI techniques to biomedical projects involving multi-modal data; design of methodology for the different project phases including conception, data-set building and curation, ground-truth extraction strategy including labeling and AI-assisted annotation tools, exploratory data analysis, customization and implementation of deep learning architectures, model training, inference and clinical validation phase.  (See more details in ).

Marco Danelutto, Full Professor at Dept. of Computer Science, Univ. of Pisa.    

Prof. Marco Danelutto obtained his PhD in Computer Science in 1990 and he is currently a full professor at the University of Pisa, Dept. of Computer Science. His main research interests are in the field of structured parallel programming models for parallel and distributed architectures. His main contribution in the field are relative a) to the development of autonomic techniques supporting management of non-functional properties in structured parallel applications, b) to the exploitation of macro data flow techniques in the implementation of parallel patterns and c) in the design of a set of parallel building blocks suitable to be used, in composition, to support

the implementation of a number of different parallel patterns. Danelutto actively participates in the design and development of FastFlow, a structured, highly efficient, parallel programming framework targeting heterogeneous multi/many core architectures. He participated in different national and international research projects, including EU FP6 CoreGRID (NoE) and GridCOMP (STREP), FP7 STREP projects ParaPhrase and Repara and H2020 RIA RePhrase. In all these projects, he has acted as WP leader and member of the project steering committee. Danelutto is the author of more than 180 papers in international refereed journals and conferences. He has been teaching different courses related to parallel/distributed computing and he is currently vice-responsible for the master’s degree in Computer science and Networking at the University of Pisa and vice-director of the Dept. of Computer Science of the Univ. of Pisa

Massimo Piccardi, professor at the Faculty of Engineering and Information Technology, University of Technology Sydney (UTS)

Massimo Piccardi is a professor of machine learning, computer vision and natural language processing (NLP) at the Faculty of Engineering and Information Technology, University of Technology Sydney (UTS). At UTS, Prof. Piccardi serves as leader for the Big Data Analytics program of the Global Big Data Technologies Centre and as Head of Discipline, Signal Processing and Analytics, in the School of Electrical and Data Engineering. Over his career, he has been the author/co-author of over a hundred and eighty scientific papers and the principal investigator in many research projects including two ARC (Australian Research Council) Discovery Projects and an ARC Linkage Project, and a chief investigator in another Linkage Project and four Linkage Infrastructure Projects. Prof Piccardi serves as an Associate Editor for journal IEEE Transactions on Big Data and is a senior member of the IEEE, a member of the IEEE Computer and Systems, Man and Cybernetis Societies and a member of the International Association for Pattern Recognition.

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