Ionel Eduard Stan is an Assistant Professor (RTD/a) at the University of Milano-Bicocca (DISCo). His research focuses on explainable and neuro-symbolic AI for time-series and multimodal signals, with applications in healthcare, telemonitoring, and smart environments. He contributes to national research programmes (currently ANTHEM/PNC; previously iNEST/PNRR) and serves the community as an Associate Editor (Neurocomputing; Frontiers in Artificial Intelligence) and as a Program Committee member and Area Chair for leading AI venues. His teaching activity includes Databases (B.Sc.), Intelligent Consumer Technologies (M.Sc.), and Foundations of Artificial Intelligence in a 2nd-level Master’s programme.
Journal Articles
Proceedings
2026 Authenticated Robotic Teleoperation with Task Recognition Stan, I., Amrani, H., Napoletano, P., D'Auria, D. (2026). Authenticated Robotic Teleoperation with Task Recognition. IEEE CONSUMER ELECTRONICS MAGAZINE, 15(1), 33-40 [10.1109/MCE.2025.3546049].2025 A Systematic Literature Review of Innovations, Challenges, and Future Directions in Telemonitoring and Wearable Health Technologies Stan, I., D'Auria, D., Napoletano, P. (2025). A Systematic Literature Review of Innovations, Challenges, and Future Directions in Telemonitoring and Wearable Health Technologies. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 1-22 [10.1109/JBHI.2025.3598056].2024 Neural-symbolic temporal decision trees for multivariate time series classification Pagliarini, G., Scaboro, S., Serra, G., Sciavicco, G., Stan, I. (2024). Neural-symbolic temporal decision trees for multivariate time series classification. INFORMATION AND COMPUTATION, 301(Part A (December 2024)), 1-22 [10.1016/j.ic.2024.105209].2023 Statistical Rule Extraction for Gas Turbine Trip Prediction Bechini, G., Losi, E., Manservigi, L., Pagliarini, G., Sciavicco, G., Stan, I., et al. (2023). Statistical Rule Extraction for Gas Turbine Trip Prediction. JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER, 145(5) [10.1115/1.4056287].2023 The voice of COVID-19: Breath and cough recording classification with temporal decision trees and random forests Manzella, F., Pagliarini, G., Sciavicco, G., Stan, I. (2023). The voice of COVID-19: Breath and cough recording classification with temporal decision trees and random forests. ARTIFICIAL INTELLIGENCE IN MEDICINE, 137(March 2023) [10.1016/j.artmed.2022.102486].2023 Fuzzy Halpern and Shoham's interval temporal logics Conradie, W., Della Monica, D., Muñoz-Velasco, E., Sciavicco, G., Stan, I. (2023). Fuzzy Halpern and Shoham's interval temporal logics. FUZZY SETS AND SYSTEMS, 456, 107-124 [10.1016/j.fss.2022.05.014].2021 Feature and language selection in temporal symbolic regression for interpretable air quality modelling Lucena-Sánchez, E., Sciavicco, G., Stan, I. (2021). Feature and language selection in temporal symbolic regression for interpretable air quality modelling. ALGORITHMS, 14(3), 1-17 [10.3390/a14030076].2019 On coarser interval temporal logics Muñoz-Velasco, E., Pelegrín, M., Sala, P., Sciavicco, G., Stan, I. (2019). On coarser interval temporal logics. ARTIFICIAL INTELLIGENCE, 266, 1-26 [10.1016/j.artint.2018.09.001].
2025 Towards Modern Rule-Based Learning Pagliarini, G., Ponsanesi, E., Sciavicco, G., Stan, I. (2025). Towards Modern Rule-Based Learning. In Short Paper Proceedings of the 6th International Workshop on Artificial Intelligence and Formal Verification, Logic, Automata, and Synthesis (pp.83-88). CEUR-WS.2024 On Modal Logic Formulae Minimization Pagliarini, G., Paradiso, A., Sciavicco, G., Stan, I. (2024). On Modal Logic Formulae Minimization. In Proceedings of the 39th Italian Conference on Computational Logic (pp.1-13). CEUR-WS.2024 ModalFP-Growth: Efficient Extraction of Modal Association Rules from Non-Tabular Data Milella, M., Pagliarini, G., Sciavicco, G., Stan, I. (2024). ModalFP-Growth: Efficient Extraction of Modal Association Rules from Non-Tabular Data. In Proceedings of the 25th Italian Conference on Theoretical Computer Science (pp.241-254). CEUR-WS.2024 Fitting’s Style Many-Valued Interval Temporal Logic Tableau System: Theory and Implementation Badia, G., Noguera, C., Paparella, A., Sciavicco, G., Stan, I. (2024). Fitting’s Style Many-Valued Interval Temporal Logic Tableau System: Theory and Implementation. In 31st International Symposium on Temporal Representation and Reasoning (TIME 2024). Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing [10.4230/LIPIcs.TIME.2024.7].2023 (Un)supervised Univariate Feature Extraction and Selection for Dimensional Data Cavina, P., Manzella, F., Pagliarini, G., Sciavicco, G., Stan, I. (2023). (Un)supervised Univariate Feature Extraction and Selection for Dimensional Data. In Proceedings of the 2nd Italian Conference on Big Data and Data Science (ITADATA 2023). CEUR-WS.2023 Heuristic Minimization Modulo Theory of Modal Decision Trees Class-Formulas Pagliarini, G., Paradiso, A., Rubin, S., Sciavicco, G., Stan, I. (2023). Heuristic Minimization Modulo Theory of Modal Decision Trees Class-Formulas. In Short Paper Proceedings of the 5th Workshop on Artificial Intelligence and Formal Verification, Logic, Automata, and Synthesis
hosted by the 22nd International Conference of the Italian Association for Artificial Intelligence (AIxIA 2023) (pp.85-92). CEUR-WS.2023 A Post-Modern Approach to Automatic Metaphor Identification Del Fante, D., Manzella, F., Sciavicco, G., Stan, E. (2023). A Post-Modern Approach to Automatic Metaphor Identification. In Proceedings of the 9th Italian Conference on Computational Linguistics (pp.1-5). CEUR-WS.2023 Efficient Modal Decision Trees Manzella, F., Pagliarini, G., Sciavicco, G., Stan, I. (2023). Efficient Modal Decision Trees. In AIxIA 2023 – Advances in Artificial Intelligence
XXIInd International Conference of the Italian Association for Artificial Intelligence, AIxIA 2023, Rome, Italy, November 6–9, 2023, Proceedings (pp.381-395). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-47546-7_26].2023 Evolutionary Explainable Rule Extraction from (Modal) Random Forests Ghiotti, M., Manzella, F., Pagliarini, G., Sciavicco, G., Stan, I. (2023). Evolutionary Explainable Rule Extraction from (Modal) Random Forests. In 26th European Conference on Artificial Intelligence, ECAI 2023 (pp.827-834). IOS Press BV [10.3233/FAIA230350].2023 A Sound and Complete Tableau System for Fuzzy Halpern and Shoham’s Interval Temporal Logic Conradie, W., Monego, R., Munoz-Velasco, E., Sciavicco, G., Stan, I. (2023). A Sound and Complete Tableau System for Fuzzy Halpern and Shoham’s Interval Temporal Logic. In 30th International Symposium on Temporal Representation and Reasoning, TIME 2023. Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing [10.4230/LIPIcs.TIME.2023.9].2023 Decision Trees with a Modal Flavor Della Monica, D., Pagliarini, G., Sciavicco, G., Stan, I. (2023). Decision Trees with a Modal Flavor. In AIxIA 2022 – Advances in Artificial Intelligence
XXIst International Conference of the Italian Association for Artificial Intelligence, AIxIA 2022, Udine, Italy, November 28 – December 2, 2022, Proceedings (pp.47-59). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-27181-6_4].2022 Neural-Symbolic Temporal Decision Trees for Multivariate Time Series Classification Pagliarini, G., Scaboro, S., Serra, G., Sciavicco, G., Stan, I. (2022). Neural-Symbolic Temporal Decision Trees for Multivariate Time Series Classification. In Leibniz International Proceedings in Informatics, LIPIcs. Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing [10.4230/LIPIcs.TIME.2022.13].2022 Multi-Models and Multi-Formulas Finite Model Checking for Modal Logic Formulas Induction Milella, M., Pagliarini, G., Paradiso, A., Stan, I. (2022). Multi-Models and Multi-Formulas Finite Model Checking for Modal Logic Formulas Induction. In Short Paper Proceedings of the 4th Workshop on Artificial Intelligence and Formal Verification, Logic, Automata, and Synthesis
hosted by the 21st International Conference of the Italian Association for Artificial Intelligence (AIxIA 2022) (pp.81-85). CEUR-WS.2022 On Modal Logic Association Rule Mining Milella, M., Munoz-Velasco, E., Pagliarini, G., Paradiso, A., Sciavicco, G., Stan, I. (2022). On Modal Logic Association Rule Mining. In Proceedings of the 23rd Italian Conference on Theoretical Computer Science (pp.53-65). CEUR-WS.2022 Statistical Rule Extraction for Gas Turbine Trip Prediction Bechini, G., Losi, E., Manservigi, L., Pagliarini, G., Sciavicco, G., Stan, I., et al. (2022). Statistical Rule Extraction for Gas Turbine Trip Prediction. In Proceedings of the ASME Turbo Expo. American Society of Mechanical Engineers (ASME) [10.1115/GT2022-82915].2021 Multi-frame modal symbolic learning Pagliarini, G., Sciavicco, G., Stan, I. (2021). Multi-frame modal symbolic learning. In Proceedings of the 3rd Workshop on Artificial Intelligence and Formal Verification, Logic, Automata, and Synthesis
hosted by the Twelfth International Symposium on Games, Automata, Logics, and Formal Verification (GandALF 2021) (pp.37-41). CEUR-WS.2021 Interval temporal random forests with an application to COVID-19 diagnosis Manzella, F., Pagliarini, G., Sciavicco, G., Stan, I. (2021). Interval temporal random forests with an application to COVID-19 diagnosis. In Leibniz International Proceedings in Informatics, LIPIcs. Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing [10.4230/LIPIcs.TIME.2021.7].2020 Towards Interval Temporal Logic Rule-Based Classification Lucena-Sánchez, E., Muñoz-Velasco, E., Sciavicco, G., Stan, I., Vaccari, A. (2020). Towards Interval Temporal Logic Rule-Based Classification. In Proceedings of the 1st Workshop on Artificial Intelligence and Formal Verification, Logic, Automata, and Synthesis
co-located with the 18th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2019) (pp.65-70). CEUR-WS.2020 A note on ultimately-periodic finite interval temporal logic model checking Monica, D., Montanari, A., Sciavicco, G., Stan, I. (2020). A note on ultimately-periodic finite interval temporal logic model checking. In Proceedings of the 2nd Workshop on Artificial Intelligence and Formal Verification, Logic, Automata, and Synthesis
hosted by the Bolzano Summer of Knowledge 2020 (BOSK 2020) (pp.11-15). CEUR-WS.2020 Time series checking with fuzzy interval temporal logics Conradie, W., della Monica, D., Munoz-Velasco, E., Sciavicco, G., Stan, I. (2020). Time series checking with fuzzy interval temporal logics. In Proceedings of the 21st Italian Conference on Theoretical Computer Science (pp.250-262). CEUR-WS.2020 Knowledge extraction with interval temporal logic decision trees Sciavicco, G., Stan, I. (2020). Knowledge extraction with interval temporal logic decision trees. In Leibniz International Proceedings in Informatics, LIPIcs (pp.1-16). Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing [10.4230/LIPIcs.TIME.2020.9].2020 Symbolic learning with interval temporal logic: The case of regression Lucena-Sanchez, E., Sciavicco, G., Stan, I. (2020). Symbolic learning with interval temporal logic: The case of regression. In Proceedings of the 2nd Workshop on Artificial Intelligence and Formal Verification, Logic, Automata, and Synthesis
hosted by the Bolzano Summer of Knowledge 2020 (BOSK 2020) (pp.5-9). CEUR-WS.2020 Rule Extraction via Dynamic Discretization with an Application to Air Quality Modelling Kamińska, J., Lucena-Sánchez, E., Sciavicco, G., Stan, I. (2020). Rule Extraction via Dynamic Discretization with an Application to Air Quality Modelling. In Proceedings of the 14th International Rule Challenge, 4th Doctoral Consortium, and 6th Industry Track @ RuleML+RR 2020
co-located with
16th Reasoning Web Summer School (RW 2020)
12th DecisionCAMP 2020 (pp.42-57). CEUR-WS.2019 Towards a General Method for Logical Rule Extraction from Time Series Sciavicco, G., Stan, I., Vaccari, A. (2019). Towards a General Method for Logical Rule Extraction from Time Series. In From Bioinspired Systems and Biomedical Applications to Machine Learning
8th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2019, Almería, Spain, June 3–7, 2019, Proceedings, Part II (pp.3-12). Springer [10.1007/978-3-030-19651-6_1].2019 Interval Temporal Logic Decision Tree Learning Brunello, A., Sciavicco, G., Stan, I. (2019). Interval Temporal Logic Decision Tree Learning. In Logics in Artificial Intelligence 16th European Conference, JELIA 2019, Rende, Italy, May 7–11, 2019, Proceedings (pp.778-793). Springer Verlag [10.1007/978-3-030-19570-0_50].2017 Implementation of a Tableau-Based Satisfiability Checker for HS3 Muñoz-Velasco, E., Sciavicco, G., Stan, I. (2017). Implementation of a Tableau-Based Satisfiability Checker for HS3. In Joint Proceedings of the 18th Italian Conference on Theoretical Computer Science and the 32nd Italian Conference on Computational Logic co-located with the 2017 IEEE International Workshop on Measurements and Networking (2017 IEEE M&N) (pp.326-340). CEUR-WS.