# Monreale Anna

Anna Monreale is an associate professor at the Computer Science Department of the University of Pisa and a member of the Knowledge Discovery and Data Mining Laboratory (KDD-Lab), a joint research group with the Information Science and Technology Institute of the National Research Council in Pisa. She has been a visiting student at Department of Computer Science of the Stevens Institute of Technology (Hoboken, NewJersey, USA) (2010). Her research interests include big data analytics, social networks and the privacy issues raising in mining these kinds of social and human sensitive data. In particular, she is interested in the evaluation of privacy risks during analytical processes and in the design of privacy-by-design technologies in the era of big data. She earned her Ph.D. in computer science from the University of Pisa in June 2011 and her dissertation was about privacy-by-design in data mining.

Topics: 

Privacy by Design in Data Analytics

Multidimensional Social Network

Discrimination in Knowledge Discovery

Spatio-temporal mining

Data Mining

2004 Bachelor Degree in Computer Science at University of Pisa with 110/110 cum laude.

2007 Master Degree in Computer Science at University of Pisa with 110/110 cum laude. Thesis: "Interpretazione Astratta per il pi-calcolo"

2011 Ph.D. in Computer Science at University of Pisa. Thesis: "Privacy by Design in Data Mining"

Position
    

Associate Professor

Affiliation
    

Department of Computer Science, University of Pisa (DI-UNIPI)

Room
    

372

Phone
    

+39 050 221 3119

Fax
    

+39 050 315 2040

Email
    

annam@di.unipi.it

Homepage
    

http://kdd.isti.cnr.it/homes/monreale/

Google Scholar
     Anna Monreale on Google Scholar 
DBLP
     Anna Monreale on DBLP 
Scopus
     Anna Monreale on Scopus 
ArnetMiner
     Anna Monreale on ArnetMiner 

### Projects

MBD - Master Big Data

DSPhD - Data Science Ph.D.

SoBigData++ - European Integrated Infrastructure for Social Mining and Big Data Analytics

XAI - Science and technology for the eXplanation of AI decision making

HumMingBird - Enhanced migration measures from a multidimensional perspective

TAILOR - Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization

HumanE-AI-Net - HumanE AI Network

SoBigData.eu - SoBigData: Social Mining and Big Data Ecosystem

MineTheNet - MineTheNet

SiemensPRA - Privacy Risk Assessment in Siemens

### Publications

### 2022

  * L. Corbucci, Monreale, A., Panigutti, C., Natilli, M., Smiraglio, S., and Pedreschi, D., “Semantic Enrichment of XAI Explanations for Healthcare”, 24th International Conference on Artificial Intelligence. 2022.
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### 2021

  * G. Mariani, Monreale, A., and Naretto, F., “Privacy Risk Assessment of Individual Psychometric Profiles”, in Discovery Science - 24th International Conference, DS 2021, Halifax, NS, Canada, October 11-13, 2021, Proceedings, 2021.
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  * M. Fontana, Naretto, F., and Monreale, A., “A new approach for cross-silo federated learning and its privacy risks”, in 18th International Conference on Privacy, Security and Trust, PST 2021, Auckland, New Zealand, December 13-15, 2021, 2021.
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  * M. Nanni, Andrienko, G., Barabasi, A. - L., Boldrini, C., Bonchi, F., Cattuto, C., Chiaromonte, F., Comandé, G., Conti, M., Coté, M., Dignum, F., Dignum, V., Domingo-Ferrer, J., Ferragina, P., Giannotti, F., Guidotti, R., Helbing, D., Kaski, K., Kertész, J., Lehmann, S., Lepri, B., Lukowicz, P., Matwin, S., Jiménez, D. Megías, Monreale, A., Morik, K., Oliver, N., Passarella, A., Passerini, A., Pedreschi, D., Pentland, A., Pianesi, F., Pratesi, F., Rinzivillo, S., Ruggieri, S., Siebes, A., Torra, V., Trasarti, R., van den Hoven, J., and Vespignani, A., “Give more data, awareness and control to individual citizens, and they will help COVID-19 containment”, 2021.
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  * M. Setzu, Guidotti, R., Monreale, A., Turini, F., Pedreschi, D., and Giannotti, F., “GLocalX - From Local to Global Explanations of Black Box AI Models”, vol. 294, p. 103457, 2021.
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### 2020

  * F. Naretto, Pellungrini, R., Nardini, F. Maria, and Giannotti, F., “Prediction and Explanation of Privacy Risk on Mobility Data with Neural Networks”, in ECML PKDD 2020 Workshops, Cham, 2020.
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  * R. Guidotti, Monreale, A., Matwin, S., and Pedreschi, D., “Black Box Explanation by Learning Image Exemplars in the Latent Feature Space”, in Machine Learning and Knowledge Discovery in Databases, Cham, 2020.
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  * F. Naretto, Pellungrini, R., Monreale, A., Nardini, F. Maria, and Musolesi, M., “Predicting and Explaining Privacy Risk Exposure in Mobility Data”, in Discovery Science, Cham, 2020.
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  * M. Setzu, Guidotti, R., Monreale, A., and Turini, F., “Global Explanations with Local Scoring”, in Machine Learning and Knowledge Discovery in Databases, Cham, 2020.
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  * B. Dong, Wang, H., Monreale, A., Pedreschi, D., Giannotti, F., and Guo, W., “Authenticated Outlier Mining for Outsourced Databases”, IEEE Transactions on Dependable and Secure Computing, vol. 17, pp. 222 - 235, 2020.
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