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2022

M. Andreani, Candila, V., and Petrella, L., “Quantile Regression Forest for Value-at-Risk Forecasting Via Mixed-Frequency Data”, Mathematical and Statistical Methods for Actuarial Sciences and Finance. Springer, Cham, 2022.

2021

M. Andreani, Candila, V., Morelli, G., and Petrella, L., “Multivariate Analysis of Energy Commodities during the COVID-19 Pandemic: Evidence from a Mixed-Frequency Approach”, Risks, vol. 9, p. 144, 2021.

In Evidence

Academic Year 2021-2022 (37th cycle)

As the Italian Ministry has decided to invest in a doctoral program on Artificial Intelligence, next year the Data Science Ph.D. will become one of the 5 nodes of a new national initiative: the National Artificial Intelligence Ph.D. All the partner institutions of the current program will join the new Ph.D.

The call for admissions to the National PhD in Artificial Intelligence is now open!

Interested in a multi-disciplinary PhD course oriented at cutting-edge research in human-centered Artificial Intelligence and its impacts on society?
Apply to one of 44 fully-funded positions at the National PhD in AI – “Society” area:

https://dottorato.unipi.it/index.php/en/application-process-for-the-acad...

Deadline: July 23, 2021, h 13:00 CET

The program is launched by the University of Pisa in partnership with:

- National Research Council - CNR
- Scuola Superiore Sant’Anna
- Scuola Normale Superiore
- Scuola IMT Lucca
- Università di Firenze
- Università di Modena e Reggio Emilia
- Università di Siena
- Università di Trento

and in collaboration with:

- Università di Bari
- Università di Bologna
- Università Cattolica del Sacro Cuore
- Università dell’Aquila
- Università degli Studi di Napoli L’Orientale
- Università di Sassari
- Università di Trieste
- INDAM (Istituto Nazionale di Alta Matematica “Francesco Severi”)
- Open Fiber SpA

This opportunity is part of the Italian National PhD Program in Artificial Intelligence.
Overall, PhD-AI.it is made of 5 federated PhD courses that bring together 61 Italian universities and research institutions. The 5 PhD courses share a common basis in the foundations and developments of AI, and each one has an area of specialisation in a strategic sector of AI application. Each PhD course is organized by a lead university, in collaboration with the National Research Council CNR:

- Health and life sciences, Università Campus Bio-Medico di Roma
- Agrifood and environment, Università degli Studi di Napoli Federico II
- Security and cybersecurity, Sapienza Università di Roma
- Industry 4.0, Politecnico di Torino
- Society, Università di Pisa

Link to the calls for admissions to all the 5 PhD course are available at
http://www.PhD-AI.it

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Publications

In Evidence

Academic Year 2021-2022 (37th cycle)