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Scatà M, Di Stefano A, La Corte A, Lio' P. Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio', Yoshua Bengio GraphĪttention Networks. Biology Įdgar Liberis Petar Velickovic, Pietro Sormanni, Michele Vendruscolo and Pietro Lio' (2018) Parapred: Antibody Paratope Prediction using Convolutional and Recurrent Neural Networks. Bruges (Belgium), 25-27 April 2018ĭi Stefano et al, Social Dynamics Modeling of Chrono-nutrition. Ioana Bica, Petar Velickovi ́c, Hui Xiao and Pietro Lio' (2018) Multi-omics data integration using cross-modal neural networks ESANN 2018 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.
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Multi-omicĪnalysis of signaling factors in inflammatory comorbidities. Hui Xiao, Krzysztof Bartoszek and Pietro Lio'. submitted to International Symposium on Molecular Logic and Computational Synthetic Biology. Olarte A Logical Framework for Modelling Breast tumorigenesis. Reasoning in Systems Biology and Medicine with Paolo Zuliani Subnetworks Enable Cross-Disease Biomarker Discovery. Hamilton, Pietro Lio', Yoshua Bengio, R Devon Hjelm Deep Petar Veličković, William Fedus, William L. At the bottom some relevant publications from the group. On the left there are methodologies, implemented in software, to analyse Big data, showing the ability to automatically learn and improve from experience without being explicitly programmed. Methods Integration: relationship between computational modeling and machine learning The figure below shows on the right, examples of modeling techniques ( a computational/mathematical model is a representation of the essential aspects of an existing system (or a system to be constructed) which presents knowledge of that system in usable form' (Eykhoff, 1974). Data integration is essential to extract all the information, including causality, about a certain subject.
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The figure below shows a variety of plots from different papers on deep learning (see at the bottom) focusing on data integration. Office: FC20 tel: +44 (0)1223-763604 E_mail: Pietro.Lio at cl.cam.ac.ukĭata Integration, cross-modality, evidence synthesis, Machine Learning in medicine I have successfully completed the equality and diversity essentials. I am happy to receive enquiries for PhD applications. In Computational Biology (Stakeholder Group for the CCBI), steering committee of CambridgeĪnd member of the Council of Clare Hall College, I am member of Ellis, the European Lab for Learning & Intelligent Systems, I am member of the Academia Europaea I am listed in xĪdmin: member of Complaint Officer/Examination Review Committee (Cambridge University) reviewer of 4 MPhils (Newcastle University), steering committee VPH-UK. Other Affliations: I am member of CAMBRIDGE CENTRE FOR AI IN MEDICINE - the IntegrateĬancer Medicine Institute, the committee of MPhil I have a MA from Cambridge, a PhD in Complex Systems and Non Linear Dynamics (School of Informatics, dept of Engineering of the Universityįirenze, Italy) and a PhD in (Theoretical) Genetics ( University Current focus is on Graph Neural Network modeling. My research interest focuses on developing Artificial Intelligence and Computational Biology models to understand diseases complexity and address personalised and precision medicine. I am a member of the Cambridge Centre for AI in Medicine.
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I am Full Professor at the department of Computer Science and Technology of the University of Cambridge and I am a member of the Artificial
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Photos on Cambridge exam "lifestyle") (HereĪfter teaching kids how to code) Pietro Liò Talk on Data ownership & Collective Awareness in the AI era, given at MYDATA 2019 Helsinki middle: work right: relax (Here