Alessandro Gianola is a (Tenure Track) Assistant Professor at the Departamento de Engenharia Informática at Instituto Superior Técnico, Universidade de Lisboa (Lisbon, Portugal), and Senior Researcher at INESC-ID. He holds a PhD in Computer Science, earned cum laude at the Free University of Bozen-Bolzano.
He works on Business Process Management (BPM), formal methods and AI: specifically, his research focuses on AI techniques and formal methods for the verification and analysis of complex processes with data, and on multi-perspective process mining.
He has co-authored more than 45 refereed publications, including articles in top-rated journals like Information Systems, the Journal of Automated Reasoning and Engineering Applications of Artificial Intelligence, and papers at premier conferences such as AAAI, IJCAI, BPM, IJCAR, ECAI, and CADE.He published a Springer Nature monograph titled ‘Verification of Data-Aware Processes via Satisfiability Modulo Theories’. His PhD dissertation won three prestigious awards: the 2022 Best Italian PhD Thesis in Theoretical Computer Science Award, the 2022 Best BPM Dissertation Award, and the 2023 CADE Bill McCune PhD Award in Automated Reasoning. Two papers that he co-authored won the Best Paper Award (PRIMA 2020 and BPM 2021)
He was/is member of the Program Committee of BPM 2023, ECAI 2023, KR 2023, IJCAI 2023, AAAI 2024, ECAI 2024, IJCAI 2024, ICPM 2024, BPM 2024, AAAI 2025, CAiSE 2025, and co-chair of the CBI/EDOC Forum 2024, workshops co-chair of FLoC 2026, and co-chair of the FM-BPM 2023 and FM-BPM 2024 workshops (co-located with the International BPM conference).
Formal Verification, BPM, Automated Reasoning, Process Mining, Computational Logic, Model Checking, Artificial Intelligence, Mathematical Logic, Theoretical Computer Science
Curriculum Vitae (28/06/2024): CV
alessandro.gianola at tecnico.ulisboa.pt
alessandro.gianola at inesc-id.pt
My scientific interests mainly involve formal methods and Business Process Management (BPM): specifically, my research activity focuses on process mining and on theoretical and methodological aspects of logic and formal methods for the verification of complex (business) processes with data.