About

My name is Andrea Perlato. I started my scientific career at the University of Verona, School of Medicine, where I investigated the neural mechanisms underlying attention and cognitive control and earned a PhD in Neuroscience.

My research combines quantitative methods, statistics, machine learning, natural language processing, and artificial intelligence to study complex biomedical and scientific data. My work spans neuroscience, scientometrics, knowledge representation, and ontology engineering, with a particular focus on developing semantic frameworks for organizing and analyzing large-scale scientific knowledge. My research has also included neurodevelopmental disorders, particularly attention-deficit/hyperactivity disorder (ADHD), integrating clinical, cognitive, and statistical approaches.

Drawing on this background, I created Inferenza to make statistical reasoning clearer and more useful for researchers working with real scientific data. The site is dedicated to applied statistics for scientific research, with a particular focus on biomedical and medical applications. Here, I explore statistical methods, the interpretation of scientific evidence, common methodological problems, and the practical use of quantitative approaches in research.

You can find more about my work on LinkedIn and ORCID, and visit my YouTube channel.

Publications

  1. Raimondi, D., Lu, F., Grun, O., Eremina, M., & Perlato, A. (2026). SCALE: Scientific Concept Aggregation via LLMs and Embeddings for Fine-Grained Taxonomy Extension. arXiv. arXiv:2608.07254
  2. de la Broise, J.-B., Bernard, N., Dubuc, J.-P., Perlato, A., & Latard, B. (2021). How to pretrain an efficient cross-disciplinary language model: The ScilitBERT use case. 2021 6th International Conference on Information Technology Research (ICITR), pp. 1–6. https://doi.org/10.1109/icitr54349.2021.9657164
  3. Perlato, A., Santandrea, E., Della Libera, C., & Chelazzi, L. (2014). Biases of attention in chronic smokers: Men and women are not alike. Cognitive, Affective, & Behavioral Neuroscience, 14(2), 742–755. https://doi.org/10.3758/s13415-014-0287-6
  4. Chelazzi, L., Perlato, A., Santandrea, E., & Della Libera, C. (2013). Rewards teach visual selective attention. Vision Research, 85, 58–72. https://doi.org/10.1016/j.visres.2012.12.005
  5. Della Libera, C., Perlato, A., & Chelazzi, L. (2011). Dissociable Effects of Reward on Attentional Learning: From Passive Associations to Active Monitoring. PLoS ONE, 6(4), e19460. https://doi.org/10.1371/journal.pone.0019460
  6. Chelazzi, L., Perlato, A., & Della Libera, C. (2010). Gains and losses adaptively adjust attentional deployment towards specific objects. Journal of Vision, 10(7), 30. https://doi.org/10.1167/10.7.30