• Associate professor at the Department of Human Science for Education, University of Milano-Bicocca, Milan
• co-founder and director of the RobotiCSS Lab – Laboratory of Robotics for the Cognitive and Social Sciences, University of Milano-Bicocca.

My page on Researchgate

As a philosopher of science, I primarily work on the methodological foundations of biorobotics, Artificial Intelligence and cognitive science. More specifically, I reconstruct and analyze the validity of methodologies involving robots and bionic systems, as well as robots interacting with animals and humans, for the study of living system behaviour and cognition.

See an article in Synthese (2020), History and Philosophy of the Life Sciences (2020), Minds and Machines (2019) and a chapter in the Springer Handbook of Model-Based Science (2017) for methodological reflections about biorobotics, and another article in Minds and Machines (2017) offering an in-depth analysis of the epistemic role of prosthetic systems.

My interests also concern the role of robots as tools to intervene on, and theorize about, the mechanisms of social cognition, still from a methodological perspective, and the methodological foundations of educational robotics (see an article in the IEEE Robotics and Automation Magazine, 2016, on robo-ethology).

In the past I also worked on the structure of neuroscientific and cognitive explanations, and on robo-ethics.

Representative publications

See my italian page for more publications and my CV (in Italian) for a complete list.

• E. Datteri, “Interactive Biorobotics“, in corso di pubblicazione su Synthese.
• E. Datteri, “Biological accuracy in large-scale brain simulations“, History and Philosophy of the Life Sciences, n. 42, vol. 1, 2020.
• E. Datteri, “The epistemic roles of automata from cybernetics to contemporary robotics“, Rosmini Studies, vol. 6, 2019.
• Datteri, E., Schiaffonati, V. (2019), “Robotic simulations, simulations of robots”, Minds and Machines, vol. 29, n. 1, pp. 109-125 (Scopus).
• Datteri, E. (2019), “Large-scale computer models of the brain: is there a ‘right’ level of detail?”, forthcoming in D’Alfonso, M. V., Berkich, D., On the Cognitive, Ethical, and Scientific Dimensions
  of Artificial Intelligence, Springer.
• Datteri, E. (2017), “The epistemic value of brain-machine interfaces for the study of the brain”, Minds and Machines 27:2, 287–313 (Scopus).
• Datteri, E. (2017), “Biorobotics”, in L. Magnani T. Bertolotti (eds.), Springer Handbook of Model Based Science, Springer, Heildelberg/Berlin, 817-837.
• Datteri, E., Zecca, L. (2017), “Theoretical vocabularies and styles of explanation of robot behaviours in children”, Research on Education and Media, Open Access.
• Datteri, E., Zecca, L. (2016) “The Game of Science: an Experiment in Robo-Ethology with Primary School Children”, IEEE Robotics and Automation Magazine, 23:2, 24-29 (Scopus).
• Datteri, E., Laudisa, F. (2015), “Large-scale simulations of brain mechanisms: beyond the synthetic method”, Paradigmi, 23:3, 23-46.
• Datteri, E. (2014), “Biorobotics: A Methodological Primer”. In Amigoni, F., Schiaffonati, V. (eds), Methods and Experimental Techiques in Computer Engineering, Springer, 71-86.
• Datteri, E., Laudisa, F. (2014), “Box-and-arrow explanations need not be more abstract than neuroscientific mechanism descriptions”, Frontiers in Theoretical and Philosophical Psychology,
  5:464 (doi: 10.3389/fpsyg.2014.00464; Scopus).
• Datteri, E., Zecca, L., Laudisa, F., Castiglioni, M. (2013), “Learning to explain: the role of educational robots in science education”, Themes in Science & Technology Education, 6:1, 29-38.
• Datteri, E., Laudisa, F. (2012), “Model testing, prediction and experimental protocols in neuroscience: a case study”, Studies in History and Philosophy of Science Part C: Studies in History
  and Philosophy of Biological and Biomedical Sciences, 43:3, 602-610.
• Datteri, E. (2011), “Prediction and experimental protocols in neuroscience: a case study”, in Logic
  and Philosophy of Science, 9:1, 373-379 
• Datteri, E., (2009), “Simulation experiments in bionics: a regulative methodological perspective”, Biology and Philosophy, 24:3, 301-324 (doi: 10.1007/s10539-008-9133-y; Scopus: BIOPE; ISI: 000266477800003).
• Trautteur, G., Datteri, E., Santoro, M. (2008), “Empirically testable models are needed for understanding visual prediction”, Behavioral and Brain Sciences, commentario su Nijhawan, R., “Visual Prediction: Psychophysics and neurophysiology of compensation for time delays”, 31:2, 217-218.
• Datteri, E., Tamburrini, G. (2007), “Biorobotic Experiments for the Discovery of Biological Mechanisms”, Philosophy of Science, 74:3, 409-430  (doi: 10.1086/522095; ISI: 000250832200007; Scopus).
• Tamburrini, G., Datteri, E. (2005), “Machine Experiments and Theoretical Modelling: from Cybernetic Methodology to Neuro-Robotics”, Minds and Machines, 15:3-4, 335-358 (doi: 10.1007/s11023-005-2924-x; Scopus: MMACE; ISI: 000234205000002).