News

  • Publication New paper on “RE-FIN: Retrieval-based Enrichment for Financial data” accepted at COLING-25!
  • Publication Towards the Terminator Economy: Assessing Job Exposure to AI through LLMs (2024), with Emilio Colombo, Mario Mezzanzanica and Antonio Serino preprint. Featured in La Repubblica, Radio24, Canadian HRReporter, Wired, and RaiNews24.
  • Publication Tool MERLIN, a model agnostic, global, model contrastive explainer for any classifier. Published on Decision Support Systems and available on GitHub
  • Speech “Social Media and AI: No Screen Neededs To Grow Smart”. See my speech about the impact of AI in education (with Pellai, Botturi and Wolf) IT, EN, FR
  • Teaching Students can book a live appointment here

Relevant events I’m involved in

About

I am Full Professor in Computer Science at University of Milan-Bicocca. I’m director of Master in AI and Data Analytics for Business at University of Milano-Bicocca, Italy.

Current Positions

  • [March24-present] Full Professor at University of Milan-Bicocca
  • [October24-present] Deputy Director Department of Statistics and Quantitative Methods at University of Milan-Bicocca
  • [2022-present] Director of the Master in AI and Data Analytics for Business , Italy
  • [2010-present] Member of the Scientific Committee of CRISP Research Centre, Milan, Italy

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 interpreta- tion, 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

Research team AI@CRISP-UNIMIB

“If you want to go fast go alone. If you want to go far go together”. Proud to work with brilliant phd students and researchers of our team

  • Lorenzo Malandri, Reseacher in AI and Computational Linguistics, Dept of Statistics and Quantitative Methods
  • Navid Nobani, Researcher on XAI, Dept of Statistics and Quantitative Methods at Unimib
  • Francesco Trentini, PostDoc in Economics at Unimib
  • Andrea Seveso, PostDoc in NLP, Dept of Statistics and Quantitative Methods at Unimib
  • Anna Velyka, PostDoc in NLP, Dept of Statistics and Quantitative Methods at Unimib
  • Filippo Pallucchini, PhD Student in Big Data Analytics for Business
  • Simone D’Amico, PhD Student in Big Data Analytics for Business
  • Alessia De Santo, PhD Student in Big Data Analytics for Business
  • Antonio Serino, PhD Student in Big Data Analytics for Business
  • Daniele Potertì, PhD Student in Big Data Analytics for Business
    Past members
  • Anna Giabelli, PhD in Computer Science, now Research Fellow at Istituto Mario Negri
  • Alessandro Castelnovo, PhD in Computer Science, now Data Science Manager at Intesa SanPaolo Bank

(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]

Granted Ongoing Research Projects

I have been working on the following granted reserch projects, that allow me putting my research on AI and XAI into practice. (see Project)

Education

  • [2012] PhD in Computer Science and Applications Dept of Computer Science, University of L’Aquila, Italy. Advisors: prof. Giuseppe Della Penna (University of L’Aquila, Italy) and prof. Daniele Magazzeni (King’s College London, UK). 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.

Teaching

  • [2010-present] Lecturer at University of Milano-Bicocca. Topics: Python, SQL, NoSQL Data Stores, Business Intelligence, eXplainable AI, Text Mining
  • [2010-present] Teaching Assistant at University of Milano-Bicocca. Topics: Python, Database, SQL

Please visit my Teaching page for further details

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)

  • (AICom) Associate 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)

Contact

Email (preferred): fabio.mercorio@unimib.it
Office Hours: by appointment

Fabio Mercorio
Room 2043 - U7 Building - Department of Statistics and Quantitative Methods / CRISP Research Centre, University of Milan-Bicocca Viale dell’Innovazione 10 - Milan - Italy Office: (+39) 02 644 82170