School of Computer Science and Statistics

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Trinity College Dublin
Dublin 2
Ireland

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Dr. Andrea Patane

Dr. Andrea Patane

Assistant Professor, Computer Science

Biography

Andrea is an Assistant Professor at the School of Computer Science and Statistics, Trinity College Dublin, in the discipline of Software and Systems. Before coming to Trinity, he held a postdoc position in the Department of Computer Science at the University of Oxford, where he also got his PhD while enrolled in the Autonomous Intelligent Machines and Systems Centre for Doctoral Training. Andrea's research interests centre on safety and robustness for artificial intelligence models, with a particular emphasis on healthcare applications and uncertainty. In his work he has developed formal techniques based on optimisation, stochastic process theory, and discrete mathematics for the analysis, verification and synthesis of probabilistic and deep learning techniques under a variety of different settings, including adversarial, fairness and interpretability. His current research focus centre around the further understanding of fairness, privacy and interpretability, as well as the exploitation and development of Bayesian techniques to enhance the reliability, safety and personalisation of deep learning models in medical settings.

Publications and Further Research Outputs

  • Amaradio MN, Jansen G, Costanza J, Patanè A, Branduardi P, Porro D, Nicosia G., L-lactate production in engineered Saccharomyces cerevisiae using a multistage multiobjective automated design framework., Biotechnology and bioengineering, 2023Journal Article, 2023, DOI
  • Ghiasi S, Patane A, Laurenti L, Gentili C, Scilingo EP, Greco A, Kwiatkowska M., Physiologically-Informed Gaussian Processes for Interpretable Modelling of Psycho-Physiological States., IEEE journal of biomedical and health informatics, PP, 2022Journal Article, 2022, DOI
  • Colombo D, Fernández-Álvarez J, Fernández-Álvarez J, Patané A, Semonella M, Kwiatkowska M, García-Palacios A, Cipresso P, Riva G, Botella C., Current State and Future Directions of Technology-Based Ecological Momentary Assessment and Intervention for Major Depressive Disorder: A Systematic Review. , Journal of clinical medicine, 8, (4), 2019, pE465Journal Article, 2019, DOI
  • Colombo D, Palacios AG, Alvarez JF, Patané A, Semonella M, Cipresso P, Kwiatkowska M, Riva G, Botella C., Current state and future directions of technology-based ecological momentary assessments and interventions for major depressive disorder: protocol for a systematic review., Systematic reviews, 7, (1), 2018, p233Journal Article, 2018, DOI
  • Patanè A, Santoro A, Costanza J, Carapezza G, Nicosia G., Pareto Optimal Design for Synthetic Biology., IEEE transactions on biomedical circuits and systems, 9, (4), 2015, p555-571Journal Article, 2015, DOI
  • Barker C, Kwiatkowska M, Mereacre A, Paoletti N, Patane A., Hardware-in-the-loop simulation and energy optimization of cardiac pacemakers., Annu Int Conf IEEE Eng Med Biol Soc, 2015, 2015, p7188-7191Journal Article, 2015, DOI
  • Ojha V., Jansen G., Patane A., La Magna A., Romano V., Nicosia G., Design and characterization of effective solar cells, Energy Systems, 13, (2), 2022, p355 - 382, p355-382Journal Article, 2022, DOI
  • Polymenakos K., Laurenti L., Patane A., Calliess J.-P., Cardelli L., Kwiatkowska M., Abate A., Roberts S., Safety Guarantees for Iterative Predictions with Gaussian Processes, Proceedings of the IEEE Conference on Decision and Control, 2020-December, 2020, p3187 - 3193, p3187-3193Journal Article, 2020, DOI
  • Ghiasi S., Patane A., Greco A., Laurenti L., Scilingo E.P., Kwiatkowska M., Gaussian Processes with Physiologically-Inspired Priors for Physical Arousal Recognition, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2020-July, 2020, p54 - 57, p54-57Journal Article, 2020, DOI
  • Patane A., Jansen G., Conca P., Carapezza G., Costanza J., Nicosia G., Multi-objective optimization of genome-scale metabolic models: the case of ethanol production, Annals of Operations Research, 276, (1-2), 2019, p211 - 227, p211-227Journal Article, 2019, DOI
  • Rosa S., Patane A., Lu C.X., Trigoni N., Semantic Place understanding for human-robot coexistence-Toward intelligent workplaces, IEEE Transactions on Human-Machine Systems, 49, (2), 2019, p160 - 170, p160-170Journal Article, 2019, DOI
  • Cardelli L., Kwiatkowska M., Laurenti L., Paoletti N., Patane A., Wicker M., Statistical guarantees for the robustness of Bayesian neural networks, IJCAI International Joint Conference on Artificial Intelligence, 2019-August, 2019, p5693 - 5700, p5693-5700Journal Article, 2019, DOI
  • Patane A., Kwiatkowska M., Calibrating the classifier: Siamese neural network architecture for end-to-end arousal recognition from ECG, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11331 LNCS, 2019, p1 - 13, p1-13Journal Article, 2019, DOI
  • Patane A., Santoro A., Romano V., Magna A.L., Nicosia G., Enhancing quantum efficiency of thin-film silicon solar cells by Pareto optimality, Journal of Global Optimization, 72, (3), 2018, p491 - 515, p491-515Journal Article, 2018, DOI
  • Patane A., Ghiasi S., Scilingo E.P., Kwiatkowska M., Automated Recognition of Sleep Arousal Using Multimodal and Personalized Deep Ensembles of Neural Networks, Computing in Cardiology, 2018-September, 2018Journal Article, 2018, DOI
  • Paoletti N., Patane A., Kwiatkowska M., Closed-loop quantitative verification of rate-adaptive pacemakers, ACM Transactions on Cyber-Physical Systems, 2, (4), 2018Journal Article, 2018, DOI
  • Eberz S., Lovisotto G., Patane A., Kwiatkowska M., Lenders V., Martinovic I., When Your Fitness Tracker Betrays You: Quantifying the Predictability of Biometric Features Across Contexts, Proceedings - IEEE Symposium on Security and Privacy, 2018-May, 2018, p889 - 905, p889-905Journal Article, 2018, DOI
  • Rosa S., Patane A., Lu X., Trigoni N., Commonsense: Collaborative learning of scene semantics by robots and humans, IoPARTS 2018 - Proceedings of the 2018 International Workshop on Internet of People, Assistive Robots and ThingS, 2018, p1 - 6, p1-6Journal Article, 2018, DOI
  • Patane A., Santoro A., Conca P., Carapezza G., Magna A.L., Romano V., Nicosia G., Multi-objective optimization and analysis for the design space exploration of analog circuits and solar cells, Engineering Applications of Artificial Intelligence, 62, 2017, p373 - 383, p373-383Journal Article, 2017, DOI
  • Patane A., Santoro A., Carapezza G., La Magna A., Romano V., Nicosia G., A multi-objective clonal selection algorithm for analog circuit and solar cell design, International Workshop on Artificial Immune Systems, AIS 2015/ICSI3 2015 - Systems Immunology, Immunoinformatics and Immune-computation: Immunology without Borders, Proceedings, 2016Journal Article, 2016, DOI
  • Patane A., Conca P., Carapezza G., Santoro A., Costanza J., Nicosia G., Metabolic circuit design automation by multi-objective BioCAD, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10122 LNCS, 2016, p30 - 44, p30-44Journal Article, 2016, DOI
  • Kwiatkowska M., Mereacre A., Paoletti N., Patane A., Synthesising Robust and Optimal Parameters for Cardiac Pacemakers Using Symbolic and Evolutionary Computation Techniques, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9271, 2015, p119 - 140, p119-140Journal Article, 2015, DOI
  • Benussi, Elias, Patane', Andrea, Wicker, Matthew, Laurenti, Luca, Kwiatkowska, Marta, Individual Fairness Guarantees for Neural Networks, International Joint Conferences on Artificial Intelligence Organization, 2022Conference Paper, 2022, DOI
  • Cardelli, Luca, Kwiatkowska, Marta, Laurenti, Luca, Patane, Andrea, Robustness Guarantees for Bayesian Inference with Gaussian Processes, Proceedings of the AAAI Conference on Artificial Intelligence, 33, (01), 2019, p7759-7768Journal Article, 2019, DOI
  • Eberz, Simon, Paoletti, Nicola, Roeschlin, Marc, Patani, Andrea, Kwiatkowska, Marta, Martinovic, Ivan, Broken Hearted: How To Attack ECG Biometrics, Internet Society, 2017Conference Paper, 2017, DOI
  • Patane, Andrea and Blaas, Arno and Laurenti, Luca and Cardelli, Luca and Roberts, Stephen and Kwiatkowska, Marta, Adversarial robustness guarantees for gaussian processes, Journal of Machine Learning Research, 23, 2022Journal Article, 2022
  • Wicker, Matthew and Laurenti, Luca and Patane, Andrea and Paoletti, Nicola and Abate, Alessandro and Kwiatkowska, Marta, Certification of iterative predictions in Bayesian neural networks, Uncertainty in Artificial Intelligence, 2021, pp1713--1723Conference Paper, 2021
  • Carbone, Ginevra and Wicker, Matthew and Laurenti, Luca and Patane, Andrea and Bortolussi, Luca and Sanguinetti, Guido, Robustness of bayesian neural networks to gradient-based attacks, Advances in Neural Information Processing Systems, 33, 2020, p15602--15613Journal Article, 2020
  • Wicker, Matthew and Laurenti, Luca and Patane, Andrea and Kwiatkowska, Marta, Probabilistic safety for bayesian neural networks, Conference on uncertainty in artificial intelligence, 2020, pp1198--1207Conference Paper, 2020
  • Blaas, Arno and Patane, Andrea and Laurenti, Luca and Cardelli, Luca and Kwiatkowska, Marta and Roberts, Stephen, Adversarial robustness guarantees for classification with gaussian processes, International Conference on Artificial Intelligence and Statistics, 2020, pp3372--3382Conference Paper, 2020
  • Wicker, Matthew and Laurenti, Luca and Patane, Andrea and Chen, Zhuotong and Zhang, Zheng and Kwiatkowska, Marta, Bayesian inference with certifiable adversarial robustness, International Conference on Artificial Intelligence and Statistics, 2021, pp2431--2439Conference Paper, 2021

Research Expertise

Control engineering, mechatronics and robotics, Theory of computation, Artificial intelligence and machine learning, Clinical and health psychology, Health services and systems,

Recognition

  • Best paper award at The Fourth International Conference on Machine Learning, Optimization, and Data Science
  • Fifth place at the 2018 Physionet Computing in Cardiology challenge
  • Merit-based scholarship - at University of Catania for outstanding grade average
  • Best poster award at The Oxford Computer Science Conference 2017
  • 2015 Valuable Artefacts Prize - for For HeartVerify: model-based quantitative verification of implantable cardiac pacemaker