Language:

Italiano English

Luca Piovesan

My photo

Research Fellow
Department of Science and Innovative Technologies
University of Piemonte Orientale "Amedeo Avogadro"
Viale Teresa Michel 11 - 15121 - Alessandria - Italy

Telephone:+39 0131 360 180
Email:luca.piovesan@uniupo.it
DBLP:https://dblp.uni-trier.de/pers/hd/p/Piovesan:Luca
Google Scholar:https://scholar.google.it/citations?user=DSvxufZKFFsC&hl=it
Scopus:https://www.scopus.com/authid/detail.uri?authorId=56641343800
Researchgate:https://www.researchgate.net/profile/Luca_Piovesan

Biography

  • Born in Turin in 1986.
  • Laurea degree (cum laude) in Computer Science from the University of Torino in 2012 (Thesis: "A CSP Based Approach to Plan Adaptation in Domains with Numeric Fluents", with prof. Pietro Torasso).
  • PhD in Computer Science from the University of Torino in 2016 (Thesis: "A Mixed-Initiative Knowledge-Based Decision Support Methodology for the Management of Patients affected by Comorbidities", with prof. Paolo Terenziani).
  • Postdoctoral Researcher: 2016-2019, DISIT, University of Piemonte Orientale.
  • Research Fellow: 2019-now, DISIT, University of Piemonte Orientale.

Awards

  • Springer Best Paper Award (2nd place) at IBERAMIA 2016
Top

Research

The main research interests are Artificial Intelligence, Medical Informatics, Temporal Database and Temporal Reasoning.
As regards Artificial Intelligence, my fields of interest are knowledge representation and reasoning (in particular, ontological reasoning, CSP, answer set programming, temporal reasoning, planning).
During my PhD (and later) I have concentrated my attention on the decision support in the field of Medical Informatics and, in particular, in the use of Computer-Interpretable Clinical Guidelines (CIGs) for comorbid and exceptional patients. This has involved the design of innovative knowledge-based AI techniques using/extending different forms of reasoning and the design of mixed-initiative forms of interaction between users and decision support systems.
In the very last years, I started to devote part of my research to clinical trials. In particular, the scope of my work is to design innovative computer-based approaches to collect and to analyze data coming to patients participating in clinical trials.
As regards temporal database, most of my research is devoted to the development of relational TDB techniques to cope with specific temporal phenomena. For instance, I concentrated my attention on the well-known phenomena of temporal indeterminacy (”Don’t know exactly when”) and on now-related facts.
As regards temporal reasoning, besides its application on Medical Informatics, I worked at several approaches aiming at extending traditional methodologies (STP – Simple Temporal Problems) to cope in an integrated way with additional phenomena, such as probabilities and preferences.

Top

Pubblications

Filter publications by topic:

Journal Articles

  • [j13] Luca Anselma, Alessandro Mazzei, Luca Piovesan and Paolo Terenziani, Reasoning and Querying Bounds on Differences with Layered Preferences, 2021, International Journal of Intelligent Systems, (accepted). Wiley. DOI: 10.1002/int.22369.
  • [j12] Luca Piovesan, Paolo Terenziani, Daniele Theseider Dupré, Conformance Analysis for Comorbid Patients in Answer Set Programming, 2020, Journal of Biomedical Informatics, 103. Elsevier. DOI:10.1016/j.jbi.2020.103377.
  • [j11] Luca Anselma, Luca Piovesan*, Paolo Terenziani, Dealing with Temporal Indeterminacy in Relational Databases: an AI methodology, 2019, AI Communications 32(3), pp. 207-221. IOS Press. DOI: 10.3233/AIC-190619 ISSN: 0921-7126.
  • [j10] Alessio Bottrighi, Luca Piovesan*, Paolo Terenziani, Supporting the Distributed Execution of Clinical Guidelines by Multiple Agents, 2019, Artificial Intelligence in Medicine 98, pp. 87-108. Elsevier. DOI:10.1016/j.artmed.2019.05.001 ISSN: 0933-3657.
  • [j9] Luca Piovesan*, Matteo Spiotta, Paolo Terenziani, Daniele Theseider Dupré, ASP for Conformance Analysis and Explanation of Clinical Guidelines Execution, 2018, Künstliche Intelligenz 32, pp. 2-3. Springer. DOI: 10.1007/s13218-018-0540-1 ISSN: 0933-1875.
  • [j8] Luca Anselma, Luca Piovesan*, Bela Stantic, Paolo Terenziani, Representing and querying now-relative relational medical data, 2018, Artificial Intelligence in Medicine 86, pp. 33-52. Elsevier. DOI:10.1016/j.artmed.2018.01.004 ISSN: 0933-3657.
  • [j7] Luca Piovesan, Gianpaolo Molino, Paolo Terenziani, GLARE-SSCPM: an Intelligent System to Support the Treatment of Comorbid Patients, 2018, IEEE Intelligent Systems (IS) 33(6), pp. 37-46. IEEE Computer Society Press. DOI: 10.1109/MIS.2018.111144734, ISSN: 1541-1672.
  • [j6] Paolo Terenziani, Antonella Andolina, Luca Piovesan, Managing Temporal Constraints with Preferences: Representation, Reasoning, and Querying, 2017, IEEE Transactions on Knowledge and Data Engineering (TKDE) 29(9), pp. 2067-2071. IEEE Computer Society Press. DOI: 10.1109/TKDE.2017.2697852, ISSN: 1041-4347.
  • [j5] Luca Anselma, Luca Piovesan*, Paolo Terenziani, Temporal detection and analysis of guideline interactions, 2017, Artificial Intelligence in Medicine 76, pp. 40-62. Elsevier. DOI: 10.1016/j.artmed.2017.01.001, ISSN: 0933-3657.
  • [j4] Luca Anselma, Luca Piovesan*, Abdul Sattar, Bela Stantic, Paolo Terenziani, A comprehensive approach to 'Now' in temporal relational databases: Semantics and Representation, 2016, IEEE Transactions on Knowledge and Data Engineering (TKDE) 28(10), pp. 2538-2551. IEEE Computer Society Press. DOI:10.1109/TKDE.2016.2588490, ISSN: 1041-4347.
  • [j3] Alessio Bottrighi, Giorgio Leonardi, Luca Piovesan*, Paolo Terenziani, Knowledge-Based Support to the Treatment of Exceptions in Computer Interpretable Clinical Guidelines, 2016, International Journal of Knowledge-Based Organizations (IJKBO), 6(3), pp. 1-27. IGI Global. DOI: 10.4018/IJKBO.2016070101, ISSN: 2155-6393.
  • [j2] Luca Anselma, Luca Piovesan*, Paolo Terenziani, A 1NF temporal relational model and algebra coping with valid-time temporal indeterminacy, 2016, Journal of Intelligent Information Systems 47(3), pp. 345-374. Springer. DOI: 10.1007/s10844-015-0367-2, ISSN: 0925-9902.
  • [j1] Luca Piovesan, Gianpaolo Molino, Paolo Terenziani, An ontological knowledge and multiple abstraction level decision support system in healthcare, 2014, Decision Analytics 1(8), pp. 1-24. Springer. DOI:10.1007/978-3-319-26585-8_7, ISSN: 2193-8636.

Conference Papers

  • [c17] Alessio Bottrighi, Gianpaolo Molino, Luca Piovesan* and Paolo Terenziani, Simulating Clinical Guidelines for Medical Education, 2019, Proceedings of 4th International Conference on Information and Education Innovations (ICIEI), pp. 66-72. Association for Computing Machinery. DOI:10.1145/3345094.3345099 ISBN:978-1-4503-7169-8.
  • [c16] Alessio Bottrighi, Luca Piovesan* and Paolo Terenziani, Run-time support to comorbidities in GLARE-SSCPM, 2019, Proceedings of 12th International Conference on Health Informatics (HEALTHINF), pp. 498-505. Science and Technology Publications (SCITEPRESS). DOI:10.5220/0007685004980505, ISBN: 978-989-758-353-7.
  • [c15] Alessio Bottrighi, Luca Piovesan* and Paolo Terenziani, Towards an “operational” educational model in healthcare: exploiting Computer-Interpretable Guidelines, 2019, Proceedings of 12th International Conference on Health Informatics (HEALTHINF), pp. 402-409. Science and Technology Publications (SCITEPRESS). DOI: 10.5220/0007482604020409, ISBN: 978-989-758-353-7.
  • [c14] Luca Anselma, Alessandro Mazzei, Luca Piovesan* and Paolo Terenziani Temporal Reasoning with Layered Preferences, 2018, International Symposium on Intelligent Systems (ISMIS), pp. 367-376. Lecture Notes in Computer Science 11177. Springer International Publishing Switzerland. DOI:10.1007/978-3-030-01851-1_35, ISBN: 978-3-030-01850-4.
  • [c13] Antonella Andolina, Luca Anselma, Luca Piovesan* and Paolo Terenziani Querying probabilistic temporal constraints for guideline interaction analysis: GLAREs approach, 2018, Ibero-American Conference on Artificial Intelligence (IBERAMIA), pp. 3-15. Lecture Notes in Computer Science 11238. Springer International Publishing Switzerland. DOI: 10.1007/978-3-030-03928-8_2, ISBN: 978-3-030-03927-1.
  • [c12] Luca Anselma, Luca Piovesan* and Paolo Terenziani An AI Approach to Temporal Indeterminacy in Relational Databases, 2018, Ibero-American Conference on Artificial Intelligence (IBERAMIA), pp. 16-28. Lecture Notes in Computer Science 11238. Springer International Publishing Switzerland. DOI:10.1007/978-3-030-03928-8_1, ISBN: 978-3-030-03927-1.
  • [c11] Alessio Bottrighi, Luca Piovesan* and Paolo Terenziani Supporting Multiple Agents in the Execution of Clinical Guidelines, 2018, Proceedings of 11th International Conference on Health Informatics (HEALTHINF), pp. 208-219. Science and Technology Publications (SCITEPRESS). DOI:10.5220/0006654802080219, ISBN: 978-989-758-281-3.
  • [c10] Luca Piovesan*, Paolo Terenziani and Daniele Theseider Dupré, Temporal Conformance Analysis and Explanation on Comorbid Patients, 2018, Proceedings of 11th International Conference on Health Informatics (HEALTHINF), pp. 17-26. Science and Technology Publications (SCITEPRESS). DOI:10.5220/0006535400170026, ISBN: 978-989-758-281-3.
  • [c9] Alessio Bottrighi, Luca Piovesan* and Paolo Terenziani A general framework for the distributed management of exceptions and comorbidities, 2018, Proceedings of 11th International Conference on Health Informatics (HEALTHINF), pp. 66-76. Science and Technology Publications (SCITEPRESS). DOI:10.5220/0006552800660076, ISBN: 978-989-758-281-3.
  • [c8] Luca Anselma, Luca Piovesan*, Paolo Terenziani Temporal reasoning techniques for the analysis of interactions in the treatment of comorbid patients, 2017, Proceedings of 32nd ACM SIGAPP Symposium On Applied Computing. DOI: 10.1145/3019612.3019713, ACM 978-1-4503-4486-9/17/04.
  • [c7] Luca Piovesan, Paolo Terenziani A Constraint-Based Approach for the Conciliation of Clinical Guidelines, 2016, Proceedings of Ibero-American Conference on Artificial Intelligence (IBERAMIA). Lecture Notes in Computer Science 10022. Springer International Publishing Switzerland. DOI: 10.1007/978-3-319-47955-2_7, ISBN: 978-3-319-47954-5.
  • [c6] Luca Piovesan, Paolo Terenziani A Mixed-Initiative approach to the conciliation of Clinical Guidelines for comorbid patients, 2015, Proceedings of Knowledge Representation for Health Care/Process Support and Knowledge Representation in Health Care (KR4HC/ProHealth). Lecture Notes in Computer Science 9485. Springer International Publishing Switzerland. DOI: 10.1007/978-3-319-26585-8_7, ISBN: 978-3-319-26584-1.
  • [c5] Luca Anselma, Luca Piovesan*, Abdul Sattar, Bela Stantic, Paolo Terenziani A General Approach to Represent and Query Now-Relative Medical Data in Relational Databases, 2015, Proceedings of 15th Conference on Artificial Intelligence in Medicine (AIME), pp. 327-331. Lecture Notes in Computer Science 9105. Springer International Publishing Switzerland. DOI:10.1007/978-3-319-19551-3_41, ISBN: 978-3-319-19550-6.
  • [c4] Luca Piovesan, Luca Anselma, Paolo Terenziani Temporal Detection of Guideline Interactions, 2015, Proceedings of 8th International Conference on Health Informatics (HEALTHINF), pp. 40-50. Science and Technology Publications (SCITEPRESS). DOI: 10.5220/0005186300400050, ISBN: 978-989-758-068-0.
  • [c3] Luca Piovesan, Gianpaolo Molino, Paolo Terenziani Supporting Multi-Level User-Driven Detection of Guideline Interactions, 2015, Proceedings of 8th International Conference on Health Informatics (HEALTHINF), pp. 413-422. Science and Technology Publications (SCITEPRESS). DOI:10.5220/0005217404130422, ISBN: 978-989-758-068-0.
  • [c2] Luca Anselma, Alessandro Mazzei, Luca Piovesan, Franco De Michieli Adopting STP for diet management, 2014, Proceedings of IEEE International Conference on Healthcare Informatics (ICHI), p. 371. IEEE Computer Society Press. DOI: 10.1109/ICHI.2014.66, ISBN: 978-1-4799-5701-9.
  • [c1] Paolo Terenziani, Alessio Bottrighi, Laura Giordano, Giuliana Franceschinis, Stefania Montani, Luca Piovesan, Luigi Portinale, Stefania Rubrichi, Matteo Spiotta, Daniele Theseider Dupré, Advances in the GINSENG project, 2014, Proceedings of IEEE International Conference on Healthcare Informatics (ICHI), p. 368. IEEE Computer Society Press. DOI: 10.1109/ICHI.2014.63, ISBN: 978-1-4799-5701-9

Selected Extended Papers/Books

  • [b5] Luca Piovesan, Gianpaolo Molino, Paolo Terenziani, Supporting Physicians in the Detection of the Interactions between Treatments of Co-Morbid Patients, 2018, In Information Resources Management Association, USA (eds.) Intelligent Systems: Concepts, Methodologies, Tools, and Applications, pp. 522-550. IGI Global. DOI: 10.4018/978-1-5225-5643-5.ch021, ISBN: 978-152255644-2; 1522556435;978-152255643-5.
  • [b4] Luca Anselma, Alessio Bottrighi, Luca Piovesan*, Paolo Terenziani, META-GLARE’s supports to agent coordination, 2019, BIOSTEC Revised Selected Papers, Communications in Computer and Information Science 1024. Springer, Cham. DOI: 10.1007/978-3-030-29196-9_24, ISBN: 978-3-030-29195-2.
  • [b3] Alessio Bottrighi, Luca Piovesan*, Paolo Terenziani, Coping with “exceptional” patients in META-GLARE, 2019, BIOSTEC Revised Selected Papers, Communications in Computer and Information Science 1024. Springer, Cham. DOI:10.1007/978-3-030-29196-9_16, ISBN: 978-3-030-29195-2.
  • [b2] Luca Anselma, Luca Piovesan*, Paolo Terenziani, Temporal Clinical Guidelines, 2017, In Carlo Combi, Giuseppe Pozzi, Pierangelo Veltri (eds.) Process Modeling and Management for Healthcare. CRC Press. ISBN: 978-1-1381-9665-0.
  • [b1] Luca Piovesan, Gianpaolo Molino, Paolo Terenziani, Supporting Physicians in the Detection of the Interactions between Treatments of Co-Morbid Patients, 2014, In Tavana, Ghapanchi, Talaei-Khoei (eds.) Healthcare Informatics and Analytics: Emerging Issues and Trends, pp. 165-193. IGI Global. DOI:10.4018/978-1-4666-6316-9.ch009, ISBN: 978-1-4666-6316-9.

Top

Projects

Project NameRolePeriodDescription
GLARE (GuideLine Acquisition Representation and Execution)Participant2013-nowsee http://people.unipmn.it/terenziani/index.html.en#projects
GINSENG (Clinical Guidelines Software Tools And Methodologies: Towards A Second Generation)Participant as PhD student2013-2016Computer Interpretable Guidelines (CIG) are an emerging research area, to support medical decision making through evidence-based recommendations. New challenges in the data management field have to be faced, to integrate CIG management with a proper treatment of patient data, and of other forms of medical knowledge. The “visionary” idea underlying our long-term research proposal is that, to achieve a significant step forward in the state-of-the-art, it is important to provide a homogeneous approach integrating (at least) three different aspects (which have been often considered in isolation by the Medical Informatics literature): (1) Computer Interpretable Guidelines, (2) Treatment of patient data, and (3) Treatment of “basic” medical knowledge (BMK).
Founded by Compagnia di San Paolo
Sviluppo di metodologie informatiche finalizzate alla raccolta e alla gestione di dati derivanti da studi clinici promossi dalla Fondazione Italiana Linfomi ONLUSParticipant as postdoctoral researcher.2016-2018The main goal of the project are the design and the development of computer-based techniques to support clinicians in (i) the design of the data collection workflows of clinical trials, (ii) the standardization of the data collected and (iii) the improvement of the collected data, decreasing the errors.
Founded by Fondazione Italiana Linfomi ONLUS.
Studio, Ricerca e Sviluppo di metodologie informatiche finalizzate alla raccolta a alla gestione di dati derivanti da studi clinici promossi dalla Fondazione Italiana Linfomi ONLUSPrincipal Investigator2019-nowThe main goal of the project are the design and the development of computer-based techniques to support clinicians in (i) the design of the data collection workflows of clinical trials, (ii) the standardization of the data collected and (iii) the improvement of the collected data, decreasing the errors.
Founded by Fondazione Italiana Linfomi ONLUS.
Extending ontologies for knowledge representation and reasoning: from foundations to applicationsPrincipal Investigator2019-2021Ontologies are very expressive and flexible formalisms for knowledge representation which can be used for representing knowledge in different areas, from the medical and biological ones, to the legal one. Ontologies represent a prolific research area, as well as a rapidly evolving technological field, and the aims of the project are twofold. On the one hand, it is devoted to the study of logical foundations of the Web Ontology Langauge, OWL, to extend them with metamodeling and nonmonotonic features to better suit the knowledge representation needs. On the other hand, it is intended to develop ontology-based methodologies for healthcare applications.
Founded by University of Piemonte Orientale.

Top

Professional Services

PC member

Session chair

  • Session chair at International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC) 2017 – HEALTHINF 2018 (http://www.insticc.org/Primoris/node/technicalProgram/biostec/)

Reviewer/subreviewer

  • Reviewer for Journal of Intelligent Information Systems (https://link.springer.com/journal/10844)
  • Reviewer for Network Modeling Analysis in Health Informatics and Bioinformatics Journal (https://www.springer.com/journal/13721)
  • Reviewer for Health Informatics Journal (http://journals.sagepub.com/home/jhi)
  • Reviewer for International Journal of Environmental Research and Public Health
  • International Joint Workshop Knowledge Representation for Health Care (KR4HC) & Process-oriented Information Systems in Healthcare (ProHealth) 2015
  • Artificial Intelligence in Medicine (AIME) 2017
  • ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (BCB) 2017
  • International Symposium on Temporal Representation and Reasoning (TIME) 2017
  • International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC) 2017 – HEALTHINF 2018
  • Artificial Intelligence in Medicine (AIME) 2019

Speaker

  • Speaker at IEEE International Conference on Healthcare Informatics (ICHI) 2014
  • Speaker at 8th International Conference on Health Informatics (HEALTHINF) 2015
  • Speaker at 15th Conference on Artificial Intelligence in Medicine (AIME) 2015
  • Speaker at Knowledge Representation for Health Care/Process Support and Knowledge Representation in Health Care (KR4HC/ProHealth) 2015 (@ 15th Conference on Artificial Intelligence in Medicine - AIME 2015)
  • Speaker at Knowledge Representation for Health Care/Process Support and Knowledge Representation in Health Care (KR4HC/ProHealth) 2017 (@ 16th Conference on Artificial Intelligence in Medicine - AIME 2017)
  • Speaker at 11th International Conference on Health Informatics (HEALTHINF) 2018
  • Speaker at Knowledge Representation for Health Care/Process Support and Knowledge Representation in Health Care (KR4HC/ProHealth) 2019 (@ 17th Conference on Artificial Intelligence in Medicine - AIME 2019)

Top

Teaching

Lectures

Top