Panigutti Cecilia
Cecilia Panigutti is currently enrolled in the Data Science Ph.D. program provided by Scuola Normale Superiore di Pisa, Univeristà di Pisa, CNR, IMT Lucca and Scuola Superiore Sant’Anna. She graduated in Physics of Complex Sytems at Università di Torino in 2016 with a thesis on Machine Learning approaches to Predictive Maintenance, and, after working for one year as a junior data scientist at aizoOon technology consulting, she started her Ph.D. under the supervision of Dino Pedreschi. Her research focus is on Explainable Machine Learning techniques and their applications in the health-care system.
Topics:
Explainable Machine Learning
2016 - 2017 Junior Data Scientist at aizoOn Technology Consulting
2016 Master's degree in Physics of Complex Systems at Università degli Studi di Torino, graduated with honours
2013 Bachelor degree in Physics at Università degli Studi di Torino
- Position
- Ph.D. Student
- Affiliation
- Department of Computer Science, University of Pisa (DI-UNIPI)
- Room
- 328
- Floor
- 2
- Homepage
- Google Scholar
- Cecilia Panigutti on Google Scholar
- Cecilia Panigutti on LinkedIn
Projects
Publications
2022
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, “Semantic Enrichment of XAI Explanations for Healthcare”, 24th International Conference on Artificial Intelligence. 2022.
2020
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, “Doctor XAI: an ontology-based approach to black-box sequential data classification explanations”, in Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 2020.
2019
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, “Explaining multi-label black-box classifiers for health applications”, in International Workshop on Health Intelligence, 2019.
2017
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, “Assessing the use of mobile phone data to describe recurrent mobility patterns in spatial epidemic models”, Royal Society open science, vol. 4, p. 160950, 2017.
Blog
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