Giacomo Lanciano
Data Science Ph.D. Student (Cycle 35)
Bio:
I am a Ph.D. student in Data Science, carrying out my research at ReTiS lab, Scuola Superiore Sant'Anna, under the supervision of Prof. Tommaso Cucinotta.
I received my M.Sc. in Engineering in Computer Science from Sapienza University of Rome, graduating with honors, with an award-winning thesis in Process Mining developed at Eindhoven University of Technology.
Research Interest:
My research is focusing on the intersection between Data Science and Cloud Computing, and in particular on developing data-driven methods for effectively supporting data-center operations.
Since September 2018, I am involved in the "AI4NFV" research project, a joint effort between Scuola Superiore Sant'Anna and the Vodafone group, aiming at enabling AI-driven operations in the context of NFV data-centers.
Affiliation:
Email:
Google Scholar:
Bibliography
2020
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, “Self-supervised pre-training of CNNs for flatness defect classification in the steelworks industry”, International Journal of Advances in Intelligent Informatics, vol. 6, pp. 13–22, 2020.
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, “SOM-Based Behavioral Analysis for Virtualized Network Functions”, in Proceedings of the 35th Annual ACM Symposium on Applied Computing, New York, NY, USA, 2020.
2018
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, “Aligning Partially-Ordered Process-Execution Traces and Models Using Automated Planning”, in 28th International Conference on Automated Planning and Scheduling (ICAPS 2018), 2018.
2017
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, “A Tool for Aligning Event Logs and Prescriptive Process Models through Automated Planning”, in Proceedings of the BPM Demo Track and BPM Dissertation Award co-located with 15th International Conference on Business Process Modeling (BPM 2017), 2017.
