Research

Post-Doc

  • (Nov 2023-…) Francesco Landolfi
  • (Apr 2023- …) 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
  • 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
  • (2020-2023), Danilo Numeroso, 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

  • (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 – Junior Assistant Professor, Computer Science Department, Università di Pisa
  • Daniele Castellana – Junior Assistant Professor, Dipartimento di Statistica, Informatica, Applicazioni, Università di Firenze
  • Francesco Crecchi – Research engineer, Adversarial Machine Learning
  • Andrea Cossu, Post Doc, Università di Pisa
  • Federico Errica – Research scientist, NEC Laboratories Europe
  • Elisa Ferrari – CEO and Founder, Quantabrain srl
  • Francesco Landolfi, Post Doc, Università di Pisa
  • Marco Podda – Junior Assistant Professor, Computer Science Department, Università di Pisa
  • Davide Italo Serramazza, Ph.D. student, University College Dublin
  • Andrea Valenti, Machine Learning Engineer (R&D), Camlin Italy