Below you can find the full list of my research publications including referred journals papers, conferences with proceedings, book chapters, poster presentations and extended abstracts.
Other details of my publications can be found on my Google Scholar profile (Google Scholar).
1. Cimpeanu, T., Di Stefano, A., Perret, C., & Han, T. A. (2023). “Social diversity reduces the complexity and cost of fostering fairness”. Elsevier Chaos, Solitons, & Fractals, 167, 113051. doi: 10.1016/j.chaos.2022.113051. https://doi.org/10.1016/j.chaos.2022.113051.
2. Chang, V., Doan, L. M. T., Di Stefano, A., Sun, Z., & Fortino, G. (2022). “Digital Payment Fraud Detection Methods in digital ages and Industry 4.0”. Elsevier Computers & Electrical Engineering (CAEE) - An International Journal, Computers & Electrical Engineering, 100, 107734, ISSN: 0045-7906. doi.org/10.1016/j.compeleceng.2022.10773. https://doi.org/10.1016/j.compeleceng.2022.107734.
3. Scatà, M., Di Stefano, A., La Corte, A., & Liò, P. (2020). “Multiplex Social Contagion Dynamics Model to shape and discriminate D2D content dissemination”. IEEE Transactions on Cognitive Communications and Networking, doi: 10.1109/TCCN.2020.3027697. https://ieeexplore.ieee.org/abstract/document/9209110.
4. Di Stefano, A., Scatà, M., Attanasio, B., La Corte, A., Liò, P., & Das, S. K. (2020). “A Novel Methodology for designing Policies in Mobile Crowdsensing Systems”. Elsevier, Pervasive and Mobile Computing, Vol. 67, 2020, 101230, ISSN 1574-1192, https://doi.org/10.1016/j.pmcj.2020.101230 - preprint version: arXiv:2001.06437
5. Di Stefano, A., Scatà, M., Vijayakumar, S., Angione, C., La Corte, A., & Liò, P. (2019). “Social dynamics modeling of chrono-nutrition”. PLoS computational biology, 15(1), e1006714. https://doi.org/10.1371/journal.pcbi.1006714.
6. Scatà, M., Di Stefano, A., La Corte, A., & Liò, P. (2018). “Quantifying the propagation of distress and mental disorders in social networks”. Scientific reports, 8(1), 1-12. https://doi.org/10.1038/s41598-018-23260-2 - Featured in “Le Scienze -Scientific American”: https://www.lescienze.it/2018/03/22/news/.
7. Guardo, E., Di Stefano, A., La Corte, A., Sapienza, M., & Scatà, M. (2018). “A fog computing-based IoT framework for precision agriculture”. Journal of Internet Technology, 19(5), 1401-1411. https://jit.ndhu.edu.tw/article/.
8. Scatà, M., Di Stefano, A., Liò, P., & La Corte, A. (2016). “The impact of heterogeneity and awareness in modeling epidemic spreading on multiplex networks”. Scientific reports, 6, 37105. https://doi.org/10.1038/srep37105.
9. Scatà, M., Di Stefano, A., La Corte, A., Liò, P., Catania, E., Guardo, E., & Pagano, S. (2016). “Combining evolutionary game theory and network theory to analyze human cooperation patterns”. Chaos, solitons & fractals, 91, 17-2. https://doi.org/10.1016/j.chaos.2016.04.018.
10. Giacchi, E., Corrente, S., Di Stefano, A., Greco, S., La Corte, A., & Scatá, M. (2016). “A context-aware and social model of dynamic multiple criteria preferences”. Decision Analytics, 3(1), 3. https://doi.org/10.1186/s40165-016-0020-3.
11. Di Stefano, A., Scatà, M., La Corte, A., Liò, P., Catania, E., Guardo, E., & Pagano, S. (2015). “Quantifying the role of homophily in human cooperation using multiplex evolutionary game theory”. PloS one, 10(10), e0140646. https://doi.org/10.1371/journal.pone.0140646 - Featured in “Le Scienze - Scientific American”: https://www.lescienze.it/2015/10/23/news/.
12. Catania, E., Di Stefano, A., Guardo, E., La Corte, A., Pagano, S., & Scatà, M. (2015). “Energy Awareness and the Role of “Critical Mass” In Smart Cities”. Energy, 4(7), 38-43. http://www.irjes.com.
13. Di Stefano, A., La Corte, A., Leotta, M., Lió, P., & Scatá, M. (2013). “It measures like me: An IoTs algorithm in WSNs based on heuristics behavior and clustering methods”. Ad Hoc Networks, 11(8), 2637-2647. https://doi.org/10.1016/j.adhoc.2013.04.011.
Bova, P., Di Stefano, A., & Han, T. A. (2023). “Both eyes open: Vigilant Incentives help Regulatory Markets improve AI Safety”. (arXiv preprint: arXiv:2303.03174). Submitted to: Journal of Artificial Intelligence Research (JAIR).
Lachi, V., Dimitri, G., Di Stefano, A., Liò, P., Bianchini, M. & Mocenni, C. (2023). “Impact of the COVID-19 outbreak on the Italian Twitter vaccination debate: A network–based analysis”. Submitted to: IEEE Transactions on Computational Social Systems.
Spasov, S., Di Stefano, A., Liò, P., & Tang, J. (2023). “GRADE: Graph Dynamic Embedding” (arXiv preprint: arXiv:2007.08060). Submitted to: IEEE Transactions on Neural Networks and Learning Systems.
1. Di Stefano, A., Jayne, C., Angione, C. & Han, T. A. (2023). “Recognition of Behavioural Intention in Repeated Games using Machine Learning”. In ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference. MIT Press. https://direct.mit.edu/isal/proceedings/isal/35/103/116860
2. Bova, P., Di Stefano, A., & Han, T. A. (2023). “A tale of two Regulatory Markets: the role of institutional incentives in supporting sustainable Regulatory Markets for future AI systems”. ALIFE 2023 (The 2023 Conference on Artificial Life). https://direct.mit.edu/isal/proceedings/isal/35/122/116902
3. Ogbo, N. D., Cimpeanu, T., Di Stefano, A., & Han, T. A. (2022). “Shake on It: The role of Commitments and the Evolution of Coordination in Networks of Technology Firms”. In ALIFE 2022: The 2022 Conference on Artificial Life (Trento, 12-22 July 2022). MIT Press. https://direct.mit.edu/isal/proceedings/isal/41/112262
4. Spasov, S., Campbell, A., Dimitri, G. M., Di Stefano, A., Scarselli, F., & Liò, P. (2021). “TG-DGM: Clustering Brain Activity using a Temporal Graph Deep Generative Model.” (preprint: https://openreview.net/pdf/). MIDL 2021 (Medical Imaging with Deep Learning), Lübeck, 7 ‑ 9 July 2021.
5. Di Stefano, A., Maesa, D. D. F., Das, S. K., & Liò, P. (2020, January). “Resolution of Blockchain Conflicts through Heuristics-based Game Theory and Multilayer Network Modeling”. In Proceedings of the 21st International Conference on Distributed Computing and Networking (pp. 1-10). https://doi.org/10.1145/3369740.3372914
6. Di Stefano, A., Scatà, M., La Corte, A., Das, S. K., & Liò, P. (2019, April). “Improving QoE in multi-layer social sensing: A cognitive architecture and game theoretic model”. In Proceedings of the Fourth International Workshop on Social Sensing (pp. 18-23). https://doi.org/10.1145/3313294.3313384
7. Giacchi, E., Di Stefano, A., La Corte, A., & Scatà, M. (2014, November). “A dynamic context-aware multiple criteria decision making model in social networks”. In International Conference on Information Society (i-Society 2014) (pp. 157-162). IEEE. https://doi.org/10.1109/i-Society.2014.7009032
8. Scatà, M., Di Stefano, A., Giacchi, E., La Corte, A., & Liò, P. (2014, August). “The bio-inspired and social evolution of node and data in a multilayer network”. In 2014 5th International Conference on Data Communication Networking (DCNET) (pp. 1-6). IEEE. https://doi.org/10.5220/0005119600410046
9. Di Stefano, A., La Corte, A., & Scata, M. (2014, June). “Health Mining: a new data fusion and integration paradigm”. In 11th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB), Computer Laboratory, Department of Computer Science and Technology, Cambridge, UK. http://www.cussb.unisr.it/cibb2014/
10. La Corte, A., Di Stefano, A., Scatá, M., & Leotta, M. (2013, October). “A Energy-Preserving Model for Wireless Sensors Networks Based on Heuristic Self-Organized Routing”. In 2013 IEEE International Conference on Systems, Man, and Cybernetics (pp. 3198-3202). IEEE. https://doi.org/10.1109/SMC.2013.545.
1. Attanasio B., Di Stefano A., La Corte A., Scatá M. (2021). “Evolutionary Dynamics and Multiplexity for Mobile Edge Computing in a Healthcare Scenario”. In: Fortino G., Liotta A., Gravina R., Longheu A. (eds) Data Science and Internet of Things. Internet of Things (Technology, Communications and Computing). Springer, Cham. https://doi.org/10.1007/978-3-030-67197-6_2
2. Di Stefano, A., Scatà, M., La Corte, A., & Giacchi, E. (2018). “A Dynamic and Context-Aware Social Network Approach for Multiple Criteria Decision Making Through a Graph-Based Knowledge Learning”. In: Graph Theoretic Approaches for Analyzing Large-Scale Social Networks (pp. 53-74). IGI Global. https://doi.org/10.4018/978-1-5225-2814-2.ch004
3. Di Stefano, A., La Corte, A., Lió, P., & Scatá, M. (2016). “Bio-Inspired ICT for Big Data Management in Healthcare”. In: Intelligent Agents in Data-intensive Computing (pp. 1-26). Springer, Cham. https://doi.org/10.1007/978-3-319-23742-8_1
1. Di Stefano, A., Jayne, C., Angione, C. & Han, T. A. (2023). “Recognition of Behavioural Intention in Repeated Games using Machine Learning”. In ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference. MIT Press. https://direct.mit.edu/isal/proceedings/isal/35/103/116860
2. Scatà, M., Di Stefano, A., La Corte A., & Raspagliesi, M. (2018, April). “Data integration, analysis of dynamics and behaviours in social networks, knowledge extraction and diffusion: an IoP framework for prevention”. In: XV Congresso Nazionale SIMM 2018 “Health and Migration Dynamics between continuity and new need”.
3. Di Stefano, A., La Corte A., & Scatà, M. (2015, June). “A Novel Multi-Agent Social Multilayer Framework for Improving Health Information Exchange and Management”. In: International School and Conference on Network Science (NetSci 2015), Zaragoza (Spain).
4. Scatà, M., Di Stefano, A., Giacchi, E., La Corte, A., & Liò, P. (2014, August). “The bio-inspired and social evolution of node and data in a multilayer network”. In 2014 5th International Conference on Data Communication Networking (DCNET) (pp. 1-6). IEEE. https://doi.org/10.5220/0005119600410046
5. Di Stefano, A., La Corte, A., & Scata, M. (2014, June). “Health Mining: a new data fusion and integration paradigm”. In 11th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB), Computer Laboratory, Department of Computer Science and Technology, Cambridge, UK. http://www.cussb.unisr.it/cibb2014/
1. Giacchi, E., Corrente, S., Di Stefano, A., Greco, S., La Corte, A., & Scatà, M. (2015, August). “A context-aware approach of multiple criteria decision making for social network analysis”. In: 23rd International Conference on Multiple Criteria Decision Making MCDM 2015 - Bridging Disciplines, Hamburg, Germany. http://www.mcdmsociety.org/
2. Giacchi, E., Corrente, S., Di Stefano, A., Greco, S., La Corte, A., & Scatà, M. (2015, July). “A novel dynamic and social perspective of multiple criteria decision making”. In: 27th European Conference on Operation Research, University of Strathclyde, Glasgow, UK.
3. Di Stefano, A., La Corte, A., & Scata, M. (2014, June). “Health Mining: a new data fusion and integration paradigm”. In: 11th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB), Computer Laboratory, Department of Computer Science and Technology, Cambridge, UK. http://www.cussb.unisr.it/cibb2014/