Post-Doc

• (Aug 2024-…) Alessio Gravina
• (Jan 2024 – …) Valerio De Caro
• (Nov 2023-…) Francesco Landolfi
• (Apr 2023- Apr 2024) Andrea Cossu
• (Dec 2022- …) Andrea Ceni
• (Nov 2022- Jan 2023) Andrea Valenti
• (Feb 2021-Lug 2022) Daniele Castellana
• (Jun 2021-Feb 2022) Elisa Ferrari
• (Feb 2021-Jan 2022) Antonio Carta

Ph.D. students

Completed

• Memorization in Recurrent Neural Networks (2017-2020), Antonio Carta, Ph.D. in Computer Science, Università di Pisa
• A Tensor Framework for Learning in Structured Domains (2017-2020), Daniele Castellana, Ph.D. in Computer Science, Università di Pisa
• Towards Real-World Data Streams for Deep Continual Learning (2019-2022), Andrea Cossu, Data Science PhD,  Scuola Normale Superiore
• Deep Learning Safety under Non-Stationarity Assumptions (2017-2020), Francesco Crecchi, Ph.D. in Computer Science, Università di Pisa
• Bayesian Deep Learning for Graphs (2018-2021), Federico Errica, Ph.D. in Computer Science, Università di Pisa
• Convergent transcriptomic and neuroimaging signature of Autism Spectrum Disorder (2017-2020), Elisa Ferrari, Data Science PhD,  Scuola Normale Superiore
• Data-driven Methods for Data Center Operations Support (2019-2022), Giacomo Lanciano, Data Science PhD,  Scuola Normale Superiore
• Combinatorial Methods for Graph Pooling (2019-2023), Francesco Landolfi, Ph.D. in Computer Science, Università di Pisa
• Reasoning Algorithmically in Graph Neural Networks (2020-2023), Danilo Numeroso, Ph.D. in Computer Science, Università di Pisa
• Deep Learning on Graphs with Applications to the Life Sciences (2017-2020), Marco Podda, Ph.D. in Computer Science, Università di Pisa
• Deep Learning for Graphs in Context-aware Recommendation (2019-2023), Asma Sattar, Computer Science Department, Università di Pisa
• Learning Representations for Deep Neural Reasoners (2019-2022), Andrea Valenti, Ph. D. in Computer Science, Università di Pisa

In progress

• (2021-2024) Wesam Nitham Alabbasi, Computer Science Department, Università di Pisa (co-supervision)
• (2019-2022), Dario Balboni, Data Science PhD,  Scuola Normale Superiore
• (2022-2025), Alessandro Cabras, National Ph.D. in AI, Università di Pisa (co-supervision)
• (2022-2025), Eric Nuertey Coleman, Computer Science Department, Università di Pisa (co-supervision)
• (2023-2026), Niko Dalla Noce, Computer Science Department, Università di Pisa
• (2020-2023), Valerio De Caro, Computer Science Department, Università di Pisa
• (2020-2023), Alessio Gravina, Computer Science Department, Università di Pisa
• (2021-2024), Riccardo Massidda, Computer Science Department, Università di Pisa
• (2022-2025) Elia Piccoli, Computer Science Department, Università di Pisa
• (2021-2024) Reshawan Ramjattan, Computer Science Department, Università di Pisa (co-supervision)
• (2020-2023), Michele Resta, Computer Science Department, Università di Pisa
• (2021-2024), Rudy Semola, Computer Science Department, Università di Pisa (co-supervision)
• (2022-2025), Lorenzo Simone, Computer Science Department, Università di Pisa
• (2023-2026), Alessandro Trenta, National Ph.D. in AI, Università di Pisa
• (2021-2024), Edoardo Urettini, National Ph.D. in AI, Università di Pisa

Research scholarships and associates

• (Feb 2024-Oct 2024) Matteo Ninniri: Diffusion models and generative deep learning for graphs
• (Jan 2024-Aug 2024) Filippo Michelis :Causal learning for timeseries
• (Dic 2023-Jun 2024) Michele Resta: Continual learning for Neural Machine Translation
• (Nov 2023-Sept 2024) Alessio Gravina: Deep learning for temporal graphs
• (Nov 2023-Apr 2024) Danilo Numeroso: Deep learning for graphs in combinatorial optimization
• (Oct 2022-Lug 2023) Emanuele Cosenza: Engineering continual learning as a software service
• (Apr 2022-June 2022) Antonio Di Mauro: Humanistic intelligence platform for the H2020 TEACHING automotive use case
• (May 2020-Apr 2022) Davide Italo Serramazza: Multimodal data processing for video remixing
• (Mar 2021-May 2021) Elisa Ferrari: Causal analysis of COVID-19 data
• (Mar 2021-May 2021) Ruggiero Santo: Deep learning for lung ultrasound processing in COVID-19
• (Jul 2020-Oct 2020) Alessio Gravina: Deep graph networks for COVID-19 drug repurposing
• (Apr 2018-Apr 2020) Antonio Bruno: Design and development of learning models for non-isomorph structured transductions
• (Jul 2019-Dec 2019) Gioele Bertoncini: Explorative analysis of wearable sensor data
• May 2019-Oct 2019) Vlad Pandelea: Machine learning for structured data and probabilistic processes
• (Apr 2019-Oct 2019) Andrea Valenti: Deep learning for music generation
• (Nov 2017-Mar 2018) Antonio Bruno: Deep Learning for non-isomorph structured transductions
• (Aug-Nov 2017) Daniele Castellana: Design and development of generative models for learning non-isomorph transductions
• (May-Nov 2017) Marco Podda: Analysis of clonal evolution data by machine learning
• (Apr-Oct 2016) Francesco Crecchi: Analysis of biomedical signals from mobile devices by Machine Learning
• (Sept 2015-Mar 2016) Francesco Brundu: Analysis of Machine-Learning techniques and models for industrial process Big Data

Alumni

• Antonio Bruno – Graduate fellow, ISTI-CNR
• Antonio Carta – Assistant Professor, Computer Science Department, Università di Pisa
• Daniele Castellana – Assistant Professor, Dipartimento di Statistica, Informatica, Applicazioni, Università di Firenze
• Francesco Crecchi – Research engineer, Adversarial Machine Learning
• Andrea Cossu – Assistant Professor, Università di Pisa
• Federico Errica – Senior research scientist, NEC Laboratories Europe
• Elisa Ferrari – CEO and Founder, Quantabrain srl
• Francesco Landolfi – Post Doc, Università di Pisa
• Danilo Numeroso – Machine Learning Engineer (R&D), iGenius, Italy
• Marco Podda – Assistant Professor, Computer Science Department, Università di Pisa
• Michele Resta – Machine Learning Engineer (R&D), iGenius, Italy
• Asma Sattar – Assistant Professor, Prince Sultan University (PSU), Saudi Arabia
• Davide Italo Serramazza – Ph.D. student, University College Dublin
• Andrea Valenti – Machine Learning Engineer (R&D), iGenius, Italy