Beyond Macrobenchmarks: Microbenchmark-based Graph Database Evaluation.Matteo Lissandrini, Martin Brugnara, and Yannis Velegrakis.Proceedings of the Conference on Very Large Databases (PVLDB), 2018.
PDF Datasets & Code pVLDB Reproducibility
Distributed k-core decomposition and maintenance in large dynamic graphs.Sabeur Aridhi, Martin Brugnara, Yannis Velegrakis, and Alberto Montresor.
In Proc. of the 10th ACM International Conference on Distributed and Event-Based Systems, DEBS’16. ACM, Irvine, CA, June 2016.
PDF Datasets & Code
A new Markov–Dubins hybrid solver with learned decision treesCristian Consonni, Martin Brugnara, Paolo Bevilacqua, Anna Tagliaferri, and Marco FregoEngineering Applications of Artificial Intelligence 122 (2023) 106166.
An Evaluation Methodology and Experimental Comparison of Graph Databases.Matteo Lissandrini, Martin Brugnara, Yannis Velegrakis.DISI Technical Reports - DISI-17-006 — April 30th, 2017.
Understanding and Managing Complex Datasets.Advisor: Yannis Velegrakis.PhD thesis University of Trento, Italy, April 2022.
Automatic analytics and understanding of big datasets for Smart Cities.Advisor: Yannis Velegrakis.MSc thesis University of Trento, Italy, October 2017.
DIP: a dataset and process management system for big data.Advisor: Yannis Velegrakis.BSc thesis University of Trento, Italy, March 2015.
2018 - Merit Grant (Cassa Rurale Lavis - Mezzocorona - Valle di Cembra).
2016 - IEEE Smart Cities Initiative grant (IEEE).
2015 - Research Grant for Recent graduates (UniTN).
Honours and awards
2018 - Best Master student (UniTN).
2017 - Best student (1st ACM Summer School in Europe, ACM)
2016 - Best Bachelor's student (UniTN).
2013 - Winner team of the Random Hacks of Kindness - Trento.