Introduction to Computational Thinking and Data Science
Programming for Data Science
Research Methodologies
Research Methods
Research Methods
Research Methods
Biography
Researcher, lecturer, PhD.
Scientific Publications
Bakurov, I., Buzzelli, M., Schettini, R., Castelli, M., & Vanneschi, L. (2023)
Full-Reference Image Quality Expression via Genetic Programming. IEEE Transactions on Image Processing, 32, 1458-1473. https://doi.org/10.1109/TIP.2023.3244662
Bakurov, I., Buzzelli, M., Schettini, R., Castelli, M., & Vanneschi, L. (2022)
Structural similarity index (SSIM) revisited: A data-driven approach. Expert Systems with Applications, 189, 1-19. [116087]. [Advanced online publication on 27 October 2021]. https://doi.org/10.1016/j.eswa.2021.116087
Bakurov, I., Castelli, M., Fontanella, F., Scotto Di Freca, A., & Vanneschi, L. (2022)
A novel binary classification approach based on geometric semantic genetic programming. Swarm and Evolutionary Computation, 69(March), 1-12. [101028]. https://doi.org/10.1016/j.swevo.2021.101028
Bakurov, I., Buzzelli, M., Castelli, M., Schettini, R., & Vanneschi, L. (2022)
Genetic programming for structural similarity design at multiple spatial scales. In GECCO ’22. Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 911-919). (GECCO 2022 - The Genetic and Evolutionary Computation Conference, July 9-13, Boston, USA). Association for Computing Machinery (ACM). ISBN 978-1-4503-9237-2/22/07
Bakurov, I., Buzzelli, M., Castelli, M., Vanneschi, L., & Schettini, R. (2021)
General purpose optimization library (Gpol): A flexible and efficient multi-purpose optimization library in python. Applied Sciences (Switzerland), 11(11), 1-34. [4774]. https://doi.org/10.3390/app11114774
Bakurov, I; Castelli, M.; Gau, O; Fontanella, F. & Vanneschi, L. (2021)
Genetic Programming for Stacked Generalization. Swarm and Evolutionary Computation, 100913. [Advanced online publication on 26 may 2021]. https://doi.org/10.1016/j.swevo.2021.100913.
Bakurov, I., & Culotta, F. (2021)
Unemployment dynamics in Italy: a counterfactual analysis at Covid time. In B. Bertaccini, L. Fabbris, & A. Petrucci (Eds.), ASA 2021 Statistics and Information Systems for Policy Evaluation: BOOK OF SHORT PAPERS of the on-site conference (pp. 215-220). (Proceedings e report; Vol. 132). Firenze University Press. https://doi.org/10.36253/978-88-5518-461-8.40
Azzali, I., Vanneschi, L., Bakurov, I., Silva, S., Ivaldi, M., & Giacobini, M. (2020)
Towards the use of vector based GP to predict physiological time series. Applied Soft Computing Journal, 89(April), [106097]. https://doi.org/10.1016/j.asoc.2020.106097
Bakurov, I., Buzzelli, M., Castelli, M., Schettini, R., & Vanneschi, L. (2020)
Parameters optimization of the Structural Similarity Index. In London Imaging Meeting 2020: Future Colour Imaging (1 ed., Vol. 2020, pp. 19-23). (London Imaging Meeting). https://doi.org/10.2352/issn.2694-118X.2020.LIM-13
Azzali, I., Vanneschi, L., Silva, S., Bakurov, I., & Giacobini, M. (2019)
A Vectorial Approach to Genetic Programming. In N. Lourenço, T. Hu, H. Richter, L. Sekanina, & P. García-Sánchez (Eds.), Genetic Programming: 22nd European Conference, EuroGP 2019, Held as Part of EvoStar 2019, Proceedings (pp. 213-227). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11451 LNCS). Switzerland: Springer Verlag. https://doi.org/10.1007/978-3-030-16670-0_14
Bakurov, I., Castelli, M., Fontanella, F., & Vanneschi, L. (2019)
A regression-like classification system for geometric semantic genetic programming. In J. J. Merelo, J. Garibaldi, A. Linares-Barranco, K. Madani, K. Warwick, & K. Warwick (Eds.), Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) (Vol. 1, pp. 40-48). (IJCCI 2019 - Proceedings of the 11th International Joint Conference on Computational Intelligence). SciTePress.
Bakurov, I., Castelli, M., Vanneschi, L., & Freitas, M. J. (2019)
Supporting medical decisions for treating rare diseases through genetic programming. In P. Kaufmann, & P. A. Castillo (Eds.), Applications of Evolutionary Computation: 22nd International Conference, EvoApplications 2019, Held as Part of EvoStar 2019, Proceedings (pp. 187-203). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11454 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-16692-2_13. ISBN: 978-3-030-16691-5; Online ISBN: 978-3-030-16692-2
Bartashevich, P., Bakurov, I., Mostaghim, S., & Vanneschi, L. (2018)
PSO-based search rules for aerial swarms against unexplored vector fields via genetic programming. In Parallel Problem Solving from Nature – PPSN XV: 15th International Conference, 2018, Proceedings (pp. 41-53). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11101 LNCS). [15th International Conference on Parallel Problem Solving from Nature, PPSN 2018, 8 to 12 september 2018, Coimbra, Portugal] Springer Verlag. DOI: 10.1007/978-3-319-99253-2_4
Bartashevich, P., Mostaghim, S., Bakurov, I., & Vanneschi, L. (2018)
Evolving PSO algorithm design in vector fields using geometric semantic GP. In GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion (pp. 262-263). New York: Association for Computing Machinery, Inc. DOI: 10.1145/3205651.3205760
Vanneschi, L., Bakurov, I., & Castelli, M. (2017)
An initialization technique for geometric semantic GP based on demes evolution and despeciation. In 2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings (pp. 113-120). [7969303] Institute of Electrical and Electronics Engineers Inc.. DOI: 10.1109/CEC.2017.7969303