Aurora Saibene

Aurora Saibene

e-mail: aurora.saibene-at-unimib.it

DISCo (Department of Informatics, Systems and Communication)
University of Milano-Bicocca
Viale Sarca 336, Building U14

Room 1049, tel: +390264487916

Google Scholar

BIOGRAPHY

Aurora Saibene is a Post Doctoral Research Fellow at the University of Milano-Bicocca (Italy), whose research activities are mainly focused on brain computer interfacing and electrophysiological signal processing, analysis and classification.

She took her Bachelor's, Master's Degree, and PhD in Computer Science at the University of Milano-Bicocca in 2015, 2018, and 2022 respectively.

Her PhD thesis in Computer Science focused on the design of a Flexible Pipeline for Electroencephalographic Signal Processing and Management, wanting to provide a set of suggestions and technical procedures to pre-process, normalize, manage features, and classify a particularly tricky signal like the electroencephalographic (EEG) one in different contexts. She has especially focused on the field of motor movement and imagery.

Some of her research topics are listed in the following:

  • electrophysiological signal processing
  • neuroimaging data analysis
  • machine learning techniques for medical applications
  • misogynistic content detection

AFFILIATIONS

  • Milan Center for Neuroscience, NeuroMI.

PUBLICATIONS

Journals

  1. Saibene A., Corchs S., Caglioni M., and Gasparini F. (2023). EEG-Based BCIs on Motor Imagery Paradigm Using Wearable Technologies: A Systematic Review. Sensors.
  2. Saibene A., and Gasparini F. (2023). Genetic algorithm for feature selection of EEG heterogeneous data. Expert Systems with Applications.
  3. Gasparini F., Rizzi G., Saibene A., and Fersini E. (2022). Benchmark dataset of memes with text transcriptions for automatic detection of multi-modal misogynistic content. Data in Brief.
  4. Saibene A., Assale M., Giltri M. (2021). Expert Systems: Definitions, Advantages and Issues in Medical Field Applications. Expert Systems with Applications.
  5. Berlingeri M., Devoto F., Gasparini F., Saibene A., Corchs S., Clemente L., Danelli L. et al. (2019). Clustering the brain with “CluB”: A new toolbox for quantitative meta-analysis of neuroimaging data. Frontiers in Neuroscience 13: 1037.

Conference Papers

  1. Fersini E., Gasparini F., Rizzi G., Saibene A., Chulvi B., Rosso P., Lees A., and Sorensen J. (2022). SemEval-2022 Task 5: Multimedia automatic misogyny identification. Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022).
  2. Fersini E., Rizzi G., Saibene A., and Gasparini F. (2022). Misogynous MEME Recognition: A Preliminary Study. International Conference of the Italian Association for Artificial Intelligence.
  3. Saibene A., Gasparini F., and Solé-Casals J. (2022). EEG-Based BCIs for Elderly Rehabilitation Enhancement Exploiting Artificial Data. International Conference of the Italian Association for Artificial Intelligence.
  4. Saibene A., Gasparini F., and Solé-Casals J. (2022). Novel EEG-based BCIs for Elderly Rehabilitation Enhancement. Proceedings of the Italian Workshop on Artificial Intelligence for an Ageing Society 2021 co-located with 19th International Conference of the Italian Association for Artificial Intelligence (AIxIA 2021).
  5. Saibene A., Assale M., Giltri M. (2021). Addressing Digital Divide and Elderly Acceptance of Medical Expert Systems for Healthy Ageing. Proceedings of the Italian Workshop on Artificial Intelligence for an Ageing Society 2020 co-located with 19th International Conference of the Italian Association for Artificial Intelligence (AIxIA 2020).
  6. Saibene A., Gasparini F. (2020). Human-Machine Interaction: EEG Electrode and Feature Selection Exploiting Evolutionary Algorithms in Motor Imagery Tasks. CENTRIC 2020, The Thirteenth International Conference on Advances in Human-oriented and Personalized Mechanisms, Technologies, and Services.
  7. Saibene A., Gasparini F. (2019). Cognitive and Physiological Response for Health Monitoring in an Ageing Population: A Multi-modal System. International Conference on Internet Science.
  8. Saibene A. (2018). Machine Learning of Multi-channel Electroencephalographic Data. Proceedings of the AIxIA Doctoral Consortium (DC) co-located with the 17th Conference of the Italian Association for Artificial Intelligence.
  9. Saibene A., Corchs S., Daini R., Facchin A. and Gasparini F. (2018). EEG Data of Face Recognition in Case of Biological Compatible Changes: A Pilot Study on Healthy People.In Proceedings of the 15th International Joint Conference on e-Business and Telecommunications - Volume 2: ICETE, ISBN 978-989-758-319-3, pages 414-420. DOI: 10.5220/0006909105800586.

Preprints

  1. Gasparini F., Cazzaniga E., and Saibene A. (2022). Inner speech recognition through electroencephalographic signals. arXiv preprint arXiv:2210.06472.
  2. Saibene A., Corchs S., Caglioni M., and Gasparini F. (2022). The evolution of AI approaches for motor imagery EEG-based BCIs. arXiv preprint arXiv:2210.06290.
  3. Saibene A., Gasparini F. (2021). GA for feature selection of EEG heterogeneous data. arXiv preprint arXiv:2103.07117.

TEACHING

  • Tutor for the Master's degree in Artificial Intelligence for Science and Technology course Ambient Intelligence, Advanced Human-System Interfaces (A.Y. 2022/2023).
  • Contract Professor for the Bachelor's degree in Computer Science course Trattamento e Codifica di Dati Multimediali (A.Y. 2022/2023).
  • Contract Professor for the Master's degree Theory and Technology of Communication course Multimedia Data Processing (A.Y. 2021/2022).
  • Tutor for the Master's degree in Computer Science course Machine Learning (from A.Y. 2019/2020 to A.Y. 2020/2021).
  • Tutor for the Master’s degree in Computer Science course Data Technology and Machine Learning – Machine Learning module (A.Y. 2018/2019).