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Dr. Emanuele Laurenzi

Dr. Emanuele Laurenzi

Tätigkeiten an der FHNW

Dozent in den Studiengängen MSc Business Information Systems, MSc Medical Informatics, BSc in Business Information Technology, BSc in International Management, CAS AI for Business Processes
Wissenschaftlicher Mitarbeiter im Kompetenzschwerpunkt Intelligent Information Systems

Betreute Studienprojekte von Dr. Emanuele Laurenzi

Nur peer-reviewed

Keine peer-reviewed Inhalte verfügbar
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
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
Peer-reviewed

Sandhu, 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
Peer-reviewed

Egger, 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
Peer-reviewed

Prater, 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
Peer-reviewed

Hinkelmann, 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
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
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
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
Peer-reviewed

Laurenzi, 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
Peer-reviewed

Laurenzi, 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
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
Peer-reviewed

Kritikos, 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
Peer-reviewed

Laurenzi, 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
Peer-reviewed

Hinkelmann, 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
Peer-reviewed

Emmenegger, 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
Peer-reviewed

Emmenegger, 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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