Photo of Alina Patelli
    • School of Engineering and Applied Science, Aston University

      B4 7ET Birmingham

      United Kingdom

    20152019
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    Personal profile

    Research Interests

    I specialise in evolutionary computation, specifically, genetic programming and its applications in smart cities, with a focus on traffic modelling and prediction. My interests also include autonomic, knowledge-based systems as well as self-adaptation and self-organisation in computing.

    Teaching Activity

    Java Program Construction (CS2300)

    Computational Intelligence (CS4720)

    Responsibilities

    Digital & Technology Solutions Degree Apprenticeship Programme Director

    Employment

    August 2018 - present: Lecturer in Computer Science (Institute of Coding)

    May 2018 - August 2018: Postdoctoral Research Fellow (ERDF Think Beyond Data)

    March 2017 - December 2018: Research Associate (EXCELL - Excellence in Smart Cyber-Physical Systems)

    August 2015 - May 2018: Teaching Fellow (Foundations of Technology Solutions Boot-camp - Digital & Technology Solutions Degree Apprenticeship)

    August 2014 - August 2015: Programming Support Officer (EAS - Computer Science, Aston University)

    Contact Details

    Email: a.patelli2@aston.ac.uk

    Room number: MB265E

    Education/Academic qualification

    PhD

    PG Cert

    PhD

    Keywords

    • Q Science (General)
    • evolutionary computation
    • intelligent knowledge based systems
    • smart cities

    Fingerprint Dive into the research topics where Alina Patelli is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

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    Research Output 2015 2019

    • 4 Conference contribution
    • 1 Article

    Disobedience as a mechanism of change

    Burth Kurka, D., Pitt, J., Lewis, P. R., Patelli, A. & Ekart, A., 15 Jan 2019, Proceedings - 12th IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2018. IEEE, Vol. 2018-September. p. 1-10 10 p. 8613714. ( 2018 IEEE 12th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Multi agent systems
    Iron
    Specifications
    Monitoring
    Experiments

    An architecture for the autonomic curation of crowdsourced knowledge

    Patelli, A., Lewis, P. R., Ekárt, A., Wang, H., Nabney, I. T., Bennett, D., Lucas, R. & Cole, A., 1 Sep 2017, In : Cluster Computing. 20, 3, p. 2031–2046 16 p.

    Research output: Contribution to journalArticle

    Open Access
    File
    Aviators
    Brain
    Managers
    Semantics

    Gaining insights into road traffic data through genetic improvement

    Ekárt, A., Patelli, A., Lush, V. & Ilie-Zudor, E., 15 Jul 2017, GECCO '17: proceedings of the Genetic and Evolutionary Computation Conference. New York, NY (US): ACM, p. 1511-1512 2 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
    Highway accidents
    Data mining

    Autonomic curation of crowdsourced knowledge: the case of career data management

    Patelli, A., Lewis, P. R., Wang, H., Nabney, I., Bennett, D., Lucas, R. & Coles, A., 8 Dec 2016, Proceedings : 2016 International Conference on Cloud and Autonomic Computing: co-located with the Tenth IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2016), ICCAC 2016. IEEE, p. 40-49 10 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Information management
    Managers
    Aviators
    Ontology
    Processing

    Two-B or not two-B? Design patterns for hybrid metaheuristics

    Patelli, A., Bencomo, N., Ekart, A., Goldingay, H. & Lewis, P., 11 Jul 2015, GECCO Companion '15 : proceedings of the companion publication of the 2015 annual conference on Genetic and Evolutionary Computation. Silva, S. (ed.). New York, NY (US): ACM, p. 1269-1274 6 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution