Andrea Patanè

614 total citations
28 papers, 316 citations indexed

About

Andrea Patanè is a scholar working on Artificial Intelligence, Control and Systems Engineering and Experimental and Cognitive Psychology. According to data from OpenAlex, Andrea Patanè has authored 28 papers receiving a total of 316 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 8 papers in Control and Systems Engineering and 5 papers in Experimental and Cognitive Psychology. Recurrent topics in Andrea Patanè's work include Adversarial Robustness in Machine Learning (7 papers), Fault Detection and Control Systems (5 papers) and Gaussian Processes and Bayesian Inference (4 papers). Andrea Patanè is often cited by papers focused on Adversarial Robustness in Machine Learning (7 papers), Fault Detection and Control Systems (5 papers) and Gaussian Processes and Bayesian Inference (4 papers). Andrea Patanè collaborates with scholars based in United Kingdom, Italy and Netherlands. Andrea Patanè's co-authors include Marta Kwiatkowska, Michelle Semonella, Desirée Colombo, Giuseppe Riva, Azucena García‐Palacios, Cristina Botella, Javier Fernández‐Álvarez, Pietro Cipresso, Luca Laurenti and Giuseppe Nicosia and has published in prestigious journals such as Computer Methods in Applied Mechanics and Engineering, European Respiratory Journal and Biotechnology and Bioengineering.

In The Last Decade

Andrea Patanè

27 papers receiving 308 citations

Peers

Andrea Patanè

ECP

Eleni Kazantzaki Greece

Alban Maxhuni Italy

Ching-Hua Chen United States

Agnes Grünerbl Germany

Helen Rostill United Kingdom

Hillol Sarker United States

R. Porter United States

Randy Klaassen Netherlands

Tzu‐Chien Hsiao Taiwan

Justin Brooks United States

Eleni Kazantzaki Greece

Andrea Patanè

207 ×1.8

ECP

62 ×0.8

14 ×0.4

86 ×2.4

49 ×1.4

Citations per year, relative to Andrea Patanè Andrea Patanè (= 1×) peers Eleni Kazantzaki

Countries citing papers authored by Andrea Patanè

Since Specialization

Citations

This map shows the geographic impact of Andrea Patanè's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Andrea Patanè with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrea Patanè more than expected).

Fields of papers citing papers by Andrea Patanè

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrea Patanè. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Andrea Patanè. The network helps show where Andrea Patanè may publish in the future.

Co-authorship network of co-authors of Andrea Patanè

This figure shows the co-authorship network connecting the top 25 collaborators of Andrea Patanè. A scholar is included among the top collaborators of Andrea Patanè based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Andrea Patanè. Andrea Patanè is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Bortolussi, Luca, et al.. (2024). On the Robustness of Bayesian Neural Networks to Adversarial Attacks. IEEE Transactions on Neural Networks and Learning Systems. 36(4). 6679–6692. 6 indexed citations

Patanè, Andrea, et al.. (2023). A Bayesian defect-based physics-guided neural network model for probabilistic fatigue endurance limit evaluation. Computer Methods in Applied Mechanics and Engineering. 418. 116521–116521. 25 indexed citations

Costanza, Jole, et al.. (2023). L‐lactate production in engineered Saccharomyces cerevisiae using a multistage multiobjective automated design framework. Biotechnology and Bioengineering. 120(7). 1929–1952. 2 indexed citations

Patanè, Andrea, et al.. (2022). Individual Fairness Guarantees for Neural Networks. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 651–658. 9 indexed citations

Ojha, Varun, et al.. (2021). Design and characterization of effective solar cells. Energy Systems. 13(2). 355–382. 6 indexed citations

Laurenti, Luca, et al.. (2021). Certification of Iterative Predictions in Bayesian Neural Networks. arXiv (Cornell University). 2 indexed citations

Laurenti, Luca, et al.. (2020). Robustness of Bayesian Neural Networks to Gradient-Based Attacks. ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/). 33. 15602–15613. 1 indexed citations

Laurenti, Luca, Andrea Patanè, Jan-Peter Calliess, et al.. (2020). Safety Guarantees for Iterative Predictions with Gaussian Processes. Oxford University Research Archive (ORA) (University of Oxford). 3187–3193. 2 indexed citations

Colombo, Desirée, Javier Fernández‐Álvarez, Andrea Patanè, et al.. (2019). 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). 465–465. 128 indexed citations

10.

Laurenti, Luca, et al.. (2019). Robustness Quantification for Classification with Gaussian Processes.. arXiv (Cornell University). 2 indexed citations

11.

Laurenti, Luca, et al.. (2019). Global Adversarial Robustness Guarantees for Neural Networks. 1 indexed citations

12.

Colombo, Desirée, Javier Fernández‐Álvarez, Andrea Patanè, et al.. (2019). Current State and Future Directions of Technology-Based Ecological Momentary Assessment and Intervention for Major Depressive Disorder: A Systematic Review. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations

13.

Colombo, Desirée, Azucena García‐Palacios, Javier Fernández‐Álvarez, et al.. (2018). 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). 233–233. 15 indexed citations

14.

Patanè, Andrea, Shadi Ghiasi, Enzo Pasquale Scilingo, & Marta Kwiatkowska. (2018). Automated Recognition of Sleep Arousal Using Multimodal and Personalized Deep Ensembles of Neural Networks. Computing in cardiology. 45. 9 indexed citations

15.

Eberz, Simon, et al.. (2018). When Your Fitness Tracker Betrays You: Quantifying the Predictability of Biometric Features Across Contexts. Zenodo (CERN European Organization for Nuclear Research). 889–905. 17 indexed citations

16.

Patanè, Andrea, Andrea Santoro, Vittorio Romano, Antonino La Magna, & Giuseppe Nicosia. (2018). Enhancing quantum efficiency of thin-film silicon solar cells by Pareto optimality. Journal of Global Optimization. 72(3). 491–515. 2 indexed citations

17.

Rosa, Stefano, Andrea Patanè, Chris Xiaoxuan Lu, & Niki Trigoni. (2018). Semantic Place Understanding for Human–Robot Coexistence—Toward Intelligent Workplaces. IEEE Transactions on Human-Machine Systems. 49(2). 160–170. 5 indexed citations

18.

Patanè, Andrea, et al.. (2018). Multi-objective optimization of genome-scale metabolic models: the case of ethanol production. Annals of Operations Research. 276(1-2). 211–227. 23 indexed citations

19.

Patanè, Andrea, et al.. (2016). Multi-objective optimization and analysis for the design space exploration of analog circuits and solar cells. Engineering Applications of Artificial Intelligence. 62. 373–383. 8 indexed citations

20.

Bellofiore, S., et al.. (1996). Changes in respiratory drive account for the magnitude of dyspnoea during bronchoconstriction in asthmatics. European Respiratory Journal. 9(6). 1155–1159. 12 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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