Immagine
mercorio

MERCORIO FABIO

Ruolo:
Professore ordinario
Settore scientifico disciplinare:
Sistemi di elaborazione delle informazioni (IINF-05/A)
Telefono:
Stanza:
  • U07, Piano: 2, Stanza: 2043

Biografia

Fabio Mercorio is a full professor of computer science at the University of Milan-Bicocca, department. of Statistics and Quantitative Methods. He holds a PhD in Computer Science and Application in 2012 at the University of L’Aquila, Italy. He is the director of master in BI and Big Data Analytics at Bicocca. From 2020 to 2023 we was Deputy Director of the CRISP research centre. In 2019, he received the first prize at the YoungTalentAward 2019 in collaboration with Accademia Nazionale Lincei in the Computer Science, Engineering & Mathematics area. His research interests mainly include Artificial Intelligence (eXplainable AI, interpretable models, local and global interpretation, explanation through symbolic approaches), Data Science (Big Data Analytics, ontology Learning, word embedding evaluation, Large Language Models) and AI Planning [formerly] (domain-independent planning, temporal continuous planning, planning in mixed discrete-continuous domains, planning in hybrid domain). He has been involved as a PI and researcher in many national and International research projects on putting AI and Big Data into practice to support decision-making, with a particular application in labour market. He serves as PC/SPC in top-tier AI conferences (AAAI,IJCAI,ECAI). He co-authored more than 90 papers.

 

Ricerca

Current Positions

Past Positions

  • [Dec2021-Feb2024] Associate Professor at University of Milan-Bicocca
  • [2020-Ago2023] Deputy Director of the CRISP Research Centre, Italy
  • [2016-Nov2021] Assistant Professor at University of Milan-Bicocca
  • [2011-2016] PostDoc at University of Milan-Bicocca
  • [2017-2018] Partner at TabulaeX Ltd (formerly spin-out company of Unimib) working on BI and Big Data Analytics. TabulaeX is now LightCast
  • [2015-2016] Visiting Researcher at King’s College London, AI Planning Group, UK

My research interests include

  • Artificial Intelligence: explainable AI, interpretable models, local and global interpretation, explanation through symbolic approaches, fairness.
  • Data Science: Big Data Analytics, ontology Learning, word embedding evaluation, Large Language Models
  • AI Planning [formerly]: domain-independent planning, temporal continuous planning, planning in mixed discrete-continuous domains, planning in hybrid domain

(Co)-Developed Tools for Researchers

  • MERLIN is a global, model-agnostic, contrastive explainer for any tabular or text classifier. It provides contrastive explanations of how the behaviour of two machine learning models differs. It is available as a python tool on Github. Related papers: [Decision Support Systems 2023]
  • ContrXT is a model agnostic, global, time contrastive explainer for any text classifier. It is available as a python tool on Github. Related papers: [Information-Fusion-22]
  • TaxoRef is a methodology for Taxonomy Refinement via word embeddings. It allows evaluating the best embedding on the basis of their ability to represent taxonomic similarity relations. Related papers: [ECML-PKDD-21]
  • GraphDBLP is a tool that models (and enriches) DBLP as a graph database for performing graph-based queries and social network analyses. Related papers: [ECML-PKDD-19][MTAP-18]
  • UPMurphi is a tool for planning with linear and nonlinear continuous PDDL+ models with processes and events. It also handles huge state spaces through a disk-based algorithm. Related papers: [ICAPS-09][Applied Intelligence 2012]
  • DiNo A Planner built on top of UPMurphi that employs graph-based heuristics to speed-up the plan synthesis (leaded by “Planning Group” at King’s College London). Related papers: [IJCAI-16]

Education

  • [2012] Ph.D. in Computer Science and Applications, Department of Computer Science, University of L’Aquila, Italy. Topics: AI Planning, Model Checking, and Data Quality.
  • [2008] Master Degree in Computer Science and Application University of L’Aquila, Italy. Advisor: prof. Giuseppe Della Penna and prof. Daniele Magazzeni. Topics: AI Planning Control Theory and Model Checking. Maximum score/summa cum laude.

Awards

  • [2019] Research Talent Award I’ve received the first prize at the YoungTalentAward 2019 in collaboration with Accademia Nazionale Lincei in the Computer Science, Engineering & Mathematics area. “for his contribution on applying AI to labour market for describing and predicting labour market phenomena”
  • [2017] FFABR Research Grant for research productivity provided by Italian Ministry of research “Finanziamento annuale individuale delle attività base di ricerca” [Grants provided on a competitive basis aimed at funding research activities]
  • [2014] Best Paper Award at the Third International Conference on Data Technologies and Applications, Vienna, Austria, 29-31, 2014
  • [2013] Best Paper Award at the Third International Workshop, Human Computer Interaction – Knowledge Discovery 1-3 Luglio, Maribor, Slovenia, 2013

Service in International Journals (Selection)

  • (AIComAssociate Editor of AI Communications
    Reviewer for (selection):
  • Artificial Intelligence
  • Cognitive Computation
  • Applied Soft Computing
  • Applied Intelligence
  • Future Generation Computer System
  • Knowledge-Based Systems
  • Computers in Industry
  • Expert Systems with Applications

Program committee membership (Selection)

  • (AAAI) AAAI Conference on Artificial Intelligence (since 2016)
  • (IJCAI) International Joint Conference on Artificial Intelligence (since 2016)
  • (ICAPS) International Conference on Automated Planning and Scheduling (since 2016)
  • (ECML-PKDD) European Conference on Machine Learning and Data Mining (since 2020)
  • ACM/SIGAPP Symposium On Applied Computing (since 2018)
  • Data Technology and Application Conference (since 2014)

Pubblicazioni

  • Della Penna, G., Magazzeni, D., Mercorio, F., Intrigila, B. (2009). UPMurphi: A tool for universal planning on PDDL+ problems. In Proceedings of the 19th International Conference on Automated Planning and Scheduling (ICAPS 2009) (pp.106-113). AAAI Press. Dettaglio

  • Mezzanzanica, M., Boselli, R., Cesarini, M., Mercorio, F. (2015). A model-based evaluation of data quality activities in KDD. INFORMATION PROCESSING & MANAGEMENT, 51(2), 144-166 [10.1016/j.ipm.2014.07.007]. Dettaglio

  • Boselli, R., Cesarini, M., Mercorio, F., Mezzanzanica, M. (2017). Using Machine Learning for Labour Market Intelligence. In Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part III (pp.330-342). Springer Verlag [10.1007/978-3-319-71273-4_27]. Dettaglio

  • Boselli, R., Cesarini, M., Mercorio, F., Mezzanzanica, M. (2017). An AI Planning System for Data Cleaning. In Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part III (pp.349-353). Springer Verlag [10.1007/978-3-319-71273-4_29]. Dettaglio

  • Piotrowski, W., Fox, M., Long, D., Magazzeni, D., Mercorio, F. (2016). Heuristic planning for PDDL+ domains. In Proceeding of 25th International Joint Conference on Artificial Intelligence (pp.3213-3219). Palo Alto : International Joint Conferences on Artificial Intelligence. Dettaglio

Progetti di ricerca

PNRR per la Missione 4, componente 2 Investimento 1.1- Avviso 104/2022 | ISALDI: Interpretable Stock Analysis Leveraging Deep multImodal models
Anno: 2022
Bando: Bando PRIN 2022
Enti finanziatori: MINISTERO DELL'UNIVERSITA' E DELLA RICERCA (MUR)
“InPreSa: Individuazione Precoce e contenimento SARS‐siCoV‐2. Strumenti e servizi per affrontare la sfida al Covid19.”
Anno: 2020
Bando: Misura a sostegno dello sviluppo di collaborazioni per l'identificazione di terapia e sistemi di diagnostica, protezione e analisi per contrastare l'emergenza Coronavirus e altre emergenze virali del futuro - Linea 2
Enti finanziatori: REGIONE LOMBARDIA
PILLARS-PATHWAYS TO INCLUSIVE LABOUR MARKETS
Anno: 2020
Bando: Technological transformations, skills and globalization - future challenges for shared prosperity
Enti finanziatori: EUROPEAN COMMISSION
MERCORIO-Fondo per il finanziamento delle attività base di ricerca
Anno: 2017
Bando: FFABR 2017
Enti finanziatori: M.I.U.R. - MINISTERO DELL'ISTRUZIONE, DELL'UNIVERSITA' E DELLA RICERCA - UFFICIO I - Bilancio e Contabilita'. Coordinamento staff della Direzione