Dr. Emanuele Laurenzi
Dr. Emanuele Laurenzi
Activities at FHNW
- Lecturer and Senior Researcher in Intelligent and Innovative Information Systems
- Head of CAS Design Thinking for Artificial Intelligence, Head of ImpactLab.
- Researcher in the fields of Enterprise Modelling, Semantic Meta-modelling, Knowledge Representation and Reasoning (subfield of AI)
- Teacher and coach in Business Process Management, Enterprise Application Integration, Business Process & Project Management, Information Management (Bachelor)
- Teacher and coach in Innovation in the Digital Age, International Field Trip, Manager’s Shadow Project, Digitalization of Business Processes (Master)
- Coaching and supervision of Master’s Thesis and Bachelor’s Thesis
- Founder of the FHNW ImpactLab
- Responsible of the FHNW OmiLab Node
- Coordinator of the Meetup BIS’n’Beer
Areas of expertise:
- Knowledge Engineering (Semantic Web, Ontologies, Knowledge Graphs, Knowledge Processing)
- Business Process Management
- Decision Logic Modelling and Process Logic Integration
- Business-IT Alignment
Teaching Activities:
Master of Science in Business Information Systems
- Innovation in the Digital Age
- International Field Trip
- Digitalization of Business Processes
- Manager’s Shadow Project
- Master’s Thesis
Bachelor of Science in Business Information Technology
- Business Process Management
- Enterprise Application Integration
Bachelor of Science in International Management
- Business Process & Project Management
- Information Management
Consulting Activities:
- Business Processes, Information Management, Knowledge Engineering
- Knowledge Representation and Reasoning
- Ontologies and Knowledge Graphs
- Enterprise Modelling
- Semantic Meta-modeling
- Domain-Specific Modelling Language
Ph.D. Project:
- AOAME: An Agile and Ontology-Aided Meta-modeling Environment
European Research Projects:
- CloudSocket - Business and IT-Cloud Alignment for Business Process as a Service (BPaaS)
- LearnPAd - Model-Based Social Learning for Public Administrations
Inno Suisse Projects:
- Patient-Radar
- SmartCoping
- Policy Modelling
- APPRIS - Integrated Early Warning System for Procurement using Semantic Technologies
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No peer reviewed content available
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Peer reviewedBuchmann, R., Eder, J., Fill, H.-G., Frank, U., Karagiannis, D., Laurenzi, E., Mylopoulos, J., Plexousakis, D., & Santos, M. Y. (2024). Large language models: Expectations for semantics-driven systems engineering. Data & Knowledge Engineering, 152, 102324. https://doi.org/10.1016/j.datak.2024.102324
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Laurenzi, E., Meyer, D., & Moesch, P. (2024). A decision-support approach for university incubators. In K. Hinkelmann & H. Smuts (Eds.), Society 5.0. 4th International Conference, Society 5.0 2024, Moka, Mauritius, June 26–28, 2024, Revised Selected Papers (pp. 218–228). Springer. https://doi.org/10.1007/978-3-031-71412-2_16
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Peer reviewedLaurenzi, E., Mathys, A., & Martin, A. (2024). An LLM-aided Enterprise Knowledge Graph (EKG) engineering process. In R. Petrick & C. Geib (Eds.), Proceedings of the AAAI 2024 Spring Symposium Series: Vol. 3(1) (pp. 148–156). Stanford University. https://doi.org/10.1609/aaaiss.v3i1.31194
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Peer reviewedLaurenzi, E., Allan, J., Campos Macias-Hammel, N., & Stoller, S. (2024). An ontology-based meta-modelling approach for semantic-driven building management systems. In J. P. A. Almeida, C. Di Ciccio, & C. Kalloniatis (Eds.), Advanced information systems engineering workshops (pp. 200–211). Springer. https://doi.org/10.1007/978-3-031-61003-5_18
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Peer reviewedDüggelin, W., & Laurenzi, E. (2024). A knowledge graph-based decision support system for resilient supply chain networks. In J. Araújo, J. L. de la Vara, M. Y. Santos, & S. Assar (Eds.), Research challenges in information science (Vol. 1, pp. 66–81). Springer. https://doi.org/10.1007/978-3-031-59465-6_5
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Witschel, H. F., Pande, C., Martin, A., Laurenzi, E., & Hinkelmann, K. (2023). Visualisierung von Mustern für hybrides Lernen und Reasoning mit menschlicher Beteiligung. In R. Dornberger (ed.), Neue Trends in Wirtschaftsinformatik und eingesetzte Technologien. Digitale Innovation und digitale Transformation (pp. 205–217). Springer. https://doi.org/10.1007/978-3-031-32538-0_13
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Peer reviewedWitschel, H. F., Laurenzi, E., Jüngling, S., Kadvany, Y., & Trojan, A. (2023). An early warning system that combines machine learning and a rule-based approach for the prediction of cancer patients’ unplanned visits. In A. Martin, H.-G. Fill, A. Gerber, K. Hinkelmann, D. Lenat, R. Stolle, & F. van Harmelen (Eds.), Proceedings of the AAAI 2023 Spring Symposium on Challenges Requiring the Combination of Machine Learning and Knowledge Engineering (AAAI-MAKE 2023). Sun SITE Central Europe. https://irf.fhnw.ch/handle/11654/48276
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Peer reviewedRordorf, D. H.-P., Käser, J., Crego Corot, A. E., & Laurenzi, E. (2023). A hybrid intelligent approach combining machine learning and a knowledge graph to support academic journal publishers addressing the Reviewer Assignment Problem (RAP). In A. Martin, H.-G. Fill, A. Gerber, K. Hinkelmann, D. Lenat, R. Stolle, & F. Harmelen (Eds.), Proceedings of the AAAI 2023 Spring Symposium on Challenges Requiring the Combination of Machine Learning and Knowledge Engineering (AAAI-MAKE 2023) (pp. 1–19). Sun SITE, Informatik V, RWTH Aachen. https://doi.org/10.26041/fhnw-11149
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Peer reviewedSchmid, C., Laurenzi, E., Michelucci, U., & Venturini, F. (2023). Explainable AI for the olive oil industry. In K. Hinkelmann, F. J. López-Pellicer, & A. Polini (Eds.), Proceedings of the 22nd International Conference on Business Informatics Research, BIR 2023 (pp. 158–171). Springer. https://doi.org/10.1007/978-3-031-43126-5_12
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Peer reviewedMancuso, M. C., & Laurenzi, E. (2023). An approach for knowledge graphs-based user stories in agile methodologies. In K. Hinkelmann, F. J. López-Pellicer, & A. Polini (Eds.), Perspectives in Business Informatics Research. BIR 2023 (pp. 133–141). Springer. https://doi.org/10.1007/978-3-031-43126-5_10
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Peer reviewedFedeli, A., Beutling, N., Laurenzi, E., & Polini, A. (2023). Comparison of general-purpose and domain-specific modeling languages in the IoT domain: A case study from the OMiLAB community. In A. Morichetta, R. A. Buchmann, K. Sandkuhl, U. Seigerroth, M. Kirikova, C. Møller, P. Forbrig, A. Gutschmidt, A.-M. Ghiran, A. Marcelletti, F. Härer, B. Re, & B. Johansson (Eds.), Joint Proceedings of the BIR 2023 Workshops and Doctoral Consortium co-located with 22nd International Conference on Perspectives in Business Informatics Research (BIR 2023) (pp. 145–157). Sun SITE, Informatik V, RWTH Aachen. https://doi.org/10.26041/fhnw-11146
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Peer reviewedLaurenzi, E. (2023). A methodological approach for ontology-based meta-modelling. In A. Morichetta, R. A. Buchmann, K. Sandkuhl, U. Seigerroth, M. Kirikova, C. Møller, P. Forbrig, A. Gutschmidt, A.-M. Ghiran, A. Marcelletti, F. Härer, B. Re, & B. Johansson (Eds.), Joint Proceedings of the BIR 2023 Workshops and Doctoral Consortium co-located with 22nd International Conference on Perspectives in Business Informatics Research (BIR 2023) (pp. 55–64). Sun SITE, Informatik V, RWTH Aachen. https://doi.org/10.26041/fhnw-11145
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Peer reviewedSandhu, G., Kilburg, A., Martin, A., Pande, C., Witschel, H. F., Laurenzi, E., & Billing, E. (2022). Practice track: a learning tracker using digital biomarkers for autistic preschoolers. In K. Hinkelmann & A. Gerber (Eds.), Proceedings of the Society 5.0 Conference 2022 - Integrating digital world and real world to resolve challenges in business and society (pp. 219–230). https://doi.org/10.29007/m2jx
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Peer reviewedPrater, R., & Laurenzi, E. (2022). A hybrid intelligent approach for the support of higher education students in literature discovery. In A. Martin, K. Hinkelmann, H.-G. Fill, A. Gerber, D. Lenat, R. Stolle, & F. van Harmelen (Eds.), Proceedings of the AAAI 2022 Spring Symposium on Machine Learning and Knowledge Engineering for Hybrid Intelligence (AAAI-MAKE 2022). https://doi.org/10.26041/fhnw-7307
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Peer reviewedEgger, N. C., & Laurenzi, E. (2022). Value creation patterns for industry-relevant model-based cyber-physical systems. In L. Ferreira Pires, S. Hammoudi, & E. Seidewitz (Eds.), MODELSWARD 2022. 10th International Conference on Model-Driven Engineering and Software Development. Proceedings (Vol. 1, pp. 364–370). SciTePress. https://doi.org/10.5220/0010984400003119
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Witschel, H. F., Pande, C., Martin, A., Laurenzi, E., & Hinkelmann, K. (2020). Visualization of patterns for hybrid learning and reasoning with human involvement. In R. Dornberger (Ed.), New trends in business information systems and technology (pp. 193–204). Springer. https://doi.org/10.1007/978-3-030-48332-6_13
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Laurenzi, E., Hinkelmann, K., Montecchiari, D., & Goel, M. (2020). Agile visualization in design thinking. In R. Dornberger (Ed.), New trends in business information systems and technology (pp. 31–47). Springer. https://doi.org/10.1007/978-3-030-48332-6_3
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Peer reviewedHinkelmann, K., Laurenzi, E., Martin, A., Montecchiari, D., Spahic, M., & Thönssen, B. (2020). ArchiMEO: A standardized enterprise ontology based on the ArchiMate conceptual model. In S. Hammoudi, L. Ferreira Pires, & B. Selić (Eds.), Proceedings of the 8th International Conference on Model-Driven Engineering and Software Development (Vol. 1, pp. 417–424). https://doi.org/10.5220/0009000204170424
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Laurenzi, E. (2020). An agile and ontology-aided approach for domain-specific adaptations of modelling languages [University of Pretoria]. https://irf.fhnw.ch/handle/11654/42970
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Peer reviewedLaurenzi, E., Hinkelmann, K., Jüngling, S., Montecchiari, D., Pande, C., & Martin, A. (2019). Towards an assistive and pattern learning-driven process modeling approach. In A. Martin, K. Hinkelmann, A. Gerber, D. Lenat, F. van Harmelen, & P. Clark (Eds.), Proceedings of the AAAI 2019 Spring Symposium on Combining Machine Learning with Knowledge Engineering (AAAI-MAKE 2019). https://doi.org/10.26041/fhnw-6431
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Peer reviewedLaurenzi, E., Hinkelmann, K., Izzo, S., Reimer, U., & van der Merwe, A. (2018). Towards an agile and ontology-aided modeling environment for DSML adaptation. Advanced Information Systems Engineering Workshops (CAiSE 2018), 222–234. https://doi.org/10.1007/978-3-319-92898-2_19
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Peer reviewedLaurenzi, E., Hinkelmann, K., & van der Merwe, A. (2018). An agile and ontology-aided modeling environment. In R. A. Buchmann, D. Karagiannis, & M. Kirikova (Eds.), The Practice of Enterprise Modeling. 11th IFIP WG 8.1 Working Conference, PoEM 2018, Vienna, Austria, October 31-November 2, 2018, proceedings (pp. 221–237). Springer. https://doi.org/10.1007/978-3-030-02302-7_14
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Peer reviewedKritikos, K., Laurenzi, E., & Hinkelmann, K. (2018). Towards business-to-IT alignment in the cloud. In Z. Á. Mann & V. Stolz (Eds.), Advances in service-oriented and cloud computing. Workshops of ESOCC 2017, Oslo, Norway, September 27-29, 2017, revised selected papers (pp. 35–52). https://doi.org/10.1007/978-3-319-79090-9_3
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Hinkelmann, K., Laurenzi, E., Martin, A., & Thönssen, B. (2018). Ontology-based metamodeling. In R. Dornberger (Ed.), Business information systems and technology 4.0. New trends in the age of digital change (pp. 177–194). Springer. https://doi.org/10.1007/978-3-319-74322-6_12
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Peer reviewedHinkelmann, K., Kurjakovic, S., Lammel, B., Laurenzi, E., & Woitsch, R. (2017). A semantically-enhanced modelling environment for business process as a service. In G. Li & Y. Yu (Eds.), 4th International Conference on Enterprise Systems. Advances in Enterprise Systems: ES 2016 (pp. 143–152). IEEE. https://doi.org/10.1109/ES.2016.25
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Peer reviewedEmmenegger, S., Thönssen, B., Laurenzi, E., Martin, A., Zhang Sprenger, C., Hinkelmann, K., & Witschel, H. F. (2016). An Ontology-based and Case-based Reasoning supported Workplace Learning Approach. Communications in Computer and Information Science. http://hdl.handle.net/11654/24551
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Peer reviewedEmmenegger, S., Laurenzi, E., Thönssen, B., Zhang Sprenger, C., Hinkelmann, K., & Witschel, H. F. (2016). Workplace Learning - Providing Recommendations of Experts and Learning Resources in a Context-sensitive and Personalized Manner. Proceedings of Special Session on Learning Modeling in Complex Organizations (LCMO) at MODELSWARD′16. https://doi.org/10.26041/fhnw-1012
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No peer reviewed content available
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Peer reviewedLaurenzi, E. (2022). AOAME 4 Society 5.0: Towards the creation and maintenance of knowledge graphs through enterprise modelling. Society 5.0 - Integrating digital world and real world to resolve challenges in business and society. https://irf.fhnw.ch/handle/11654/43264
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Peer reviewedKurjakovic, S., Lammel, B., Laurenzi, E., Woitsch, R., & Hinkelmann, K. (2016, November 2). A Semantically-Enhanced Modelling Environment for Business Process as a Service. 4th International Conference on Enterprise Systems. http://hdl.handle.net/11654/24288
Contact
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Dr. Emanuele Laurenzi
- Lecturer, MSc Business Information Systems
- Telephone
- +41 62 957 28 26 (direct)
- ZW1hbnVlbGUubGF1cmVuemlAZmhudy5jaA==
- FHNW University of Applied Sciences and Arts Northwestern Switzerland
School of Business
Riggenbachstrasse 16
CH – 4600 Olten