Claudio Lucchese

Associate Professor with the Ca’ Foscari University of Venice
Dept. of Environmental Sciences, Informatics and Statistics
Data Mining Group at Ca’ Foscari

Contact info

E-mail :	claudio.lucchese#unive.it
Address :	Dipartimento di Scienze Ambientali, Informatica e Statistica
	Università Ca’ Foscari di Venezia
	Campus Scientiﬁco, Ediﬁcio Zeta, Studio Z.B10
	Via Torino, 155
	30170 Venezia Mestre (VE)
	ITALY
Phone :	+39 041 234 8424

Short Bio

Dr. Claudio Lucchese is associate Professor with the Università Ca’ Foscari di Venezia. Until 2017 he was a researcher with the I.S.T.I. “A. Faedo” – C.N.R. working with the High Performance Computing Lab. His main research activities are in the areas of data mining techniques for information retrieval and large-scale data processing. He has published more than 100 papers on these topics in peer reviewed international journals, conferences and other venues. He has taught courses on data mining and parallel computing at the Computer Science course of the Università Ca’ Foscari di Venezia, Università di Firenze and at the Ph.D. courses of the Università di Pisa and I.M.T. Institute for Advanced Studies Lucca. He participated to and coordinated activities in European (Sapir, Assets, InGeoClouds, SoBigData) and Italian national projects.

Bibliometric Indices

	Google Scholar	Scopus
citations	2649	1311
h-index	27	20
i10-index	55	33
no. journals	23	20

Awards

2018 (Italian) National Scientiﬁc Qualiﬁcation as Full Professor in Computer Science (01/B1) and Information Systems Engineering (09/H1) (valid until 26/07/2024).

2017 ACM CIKM Outstanding paper Reviewer.
2017 NVIDIA GPU Grant.
2016 Best Student Paper at DocEng ’16: ACM Symposium on Document Engineering[2].
2015 Best Paper Award at SIGIR ’15: ACM SIGIR Conference on Research and Development in Information Retrieval [3].
2015 ACM Notable article in computing in 2015 [3].
2013 ACM Notable article in computing in 2013 [7].
2012 Best Young Research (under 32) at the I.S.T.I. “A. Faedo” – C.N.R.
2010-2011 C.N.R. Highlights, selected among the best C.N.R. publications [8].
2011 Best Young Research (under 32) at the I.S.T.I. “A. Faedo” – C.N.R.
2010 Finalist for the Cor Baayen Award by ERCIM – The European Research Consortium for Informatics and Mathematics.

Selected Publications

[4] Lucchese, C., Nardini, F. M., Orlando, S., Perego, R., and Trani, S. Selective gradient boosting for eﬀective learning to rank. In SIGIR ’18: Proceedings of the 41th International ACM SIGIR Conference on Research and Development in Information Retrieval (2018). (acceptance 21%). GII-GRIN Class 1.
[9] Lulli, A., Carlini, E., Dazzi, P., Lucchese, C., And Ricci, L. Fast connected components computation in large graphs by vertex pruning. IEEE TPDS Transactions on Parallel and Distributed Systems, pre-print, (2016). doi.
[3] Lucchese, C., Nardini, F.M., Orlando, S., Perego, R., Tonellotto, N., And Venturini, R. Quickscorer: a fast algorithm to rank documents with additive ensembles of regression trees. In SIGIR ’15: Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval (2015). (Best Paper) (ACM Notable Article). (acceptance 20%). GII-GRIN Class 1. Citations: 15 on Google Scholar, 10 on Scopus.
[6] Lucchese, C., Orlando, S., And Perego, R. A unifying framework for mining approximate top-k binary patterns. IEEE TKDE Transactions On Knowledge and Data Engineering 26, 12 (2014), 2900–2913. Impact Factor 2.067. ANVUR Class A. Citations: 13 on Google Scholar, 8 on Scopus.
[7] Lucchese, C., Orlando, S., Perego, R., Silvestri, F., And Tolomei, G. Discovering tasks from search engine query logs. ACM TOIS Transactions on Information Systems 31, 3 (2013). (ACM Notable Article), Impact Factor 1.300. ANVUR Class A. Citations: 29 on Google Scholar, 12 on Scopus.
[1] Boley, M., Lucchese, C., Paurat, D., And Gartner, T. Direct local pattern sampling by eﬃcient two-step random procedures. In KDD ’11: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (August 21-24 2011), pp. 582–590. (acceptance 7.8%). GII-GRIN Class 1. Citations: 27 on Google Scholar, 14 on Scopus.
[8] Lucchese, C., Rayan, D., Vlachos, M., And Yu, P. S. Rights protection of trajectory datasets with nearest-neighbor preservation. VLDB Journal 19, 4 (2010), 531–556. Impact Factor 2.198. ANVUR Class 1. Citations: 12 on Google Scholar, 5 on Scopus.
[5] Lucchese, C., Orlando, S., And Perego, R. Fast and memory eﬃcient mining of frequent closed itemsets. IEEE TKDE Transactions On Knowledge and Data Engineering 18, 1 (2006), 21–36. Impact Factor 2.063. ANVUR Class 1. Citations: 212 on Google Scholar, 125 on Scopus.

Education

Ph.D. in Computer Science at the Università Ca’ Foscari di Venezia. Supervisor: prof. S. Orlando. Thesis title: “High Performance Closed Frequent Itemsets Mining Inspired by Emerging Computer Architectures”. (November 1, 2004 – October 31, 2007. Defended on February 18, 2008)
Joint Study Agreement between the Università Ca’ Foscari di Venezia and the IBM T.J. Watson Research Center at Hawthorne (New York). I spent a period of about three months under the supervision of prof. Philip S. Yu, former head of the Software Tools and Techniques Laboratory, working on the topic “watermarking of time-series databases with mining guarantees”. (May 29, 2006 – August 14, 2006)
Master Degree in Computer Science summa cum laude at the Università Ca’ Foscari di Venezia. Supervisor: prof. S. Orlando. Thesis title: “Data mining algorithms for the extraction of closed frequent itemsets”. (October 10, 2003)
Exchange Student, according to the Socrates/Erasmus program, at the Computer Science Department of the Manchester University. (February 27, 2003 – June 14, 2003)
Bachelor Degree in Computer Science summa cum laude at the Università Ca’ Foscari di Venezia. Supervisor: prof. M. Pelillo. Thesis title: “Marr vs. Canny: two algorithms for computer vision”. (February 15, 2002)

Professional Experience

01/07/2017 – today: Associate Professor at the Dipartimento di Scienze Ambientali, Informatica e Statistica– Università Ca’ Foscari di Venezia.
11/05/2007 – 30/06/2017: Researcher with the I.S.T.I. “A. Faedo” – C.N.R. in Pisa.
28/05/2012 – 30/04/2016: Consultant for Tiscali Italia S.p.A.. Topic: design and development of near-duplicate detection and document ranking algorithms for the istella^∗ Web search engine.
17/05/2015 – 07/06/2015: Visiting Scholar at the ETIS Information Processing and Systems Lab, a joint research lab of CNRS, ENSEA Cergy and University of Cergy-Pontoise, working with Prof. Dimitris Kotzinos, head of the Multimedia Indexation and Data Integration Lab. Research Topic: mining of RDF graphs.
02/22/2007 – 11/04/2007: Research Associate at the I.S.T.I. “A. Faedo” – C.N.R., with the High Performance Computing Laboratory.
11/09/2006 – 11/28/2006: Research Collaboration with the I.S.T.I. “A. Faedo” – C.N.R. within the internal project “P3D: Privacy Preserving Pattern Discovery”, for the supervision of the implementation of the ConQueSt system for the constraint-based discovery of patterns, in collaboration with the Knowledge Discovery and Delivery (KDD) and High Performance Computing (HPC) laboratories.
01/01/2006 – 01/31/2006: Research Collaboration with the Università di Pisa within the national project “Geo-PKDD: Geographic Privacy-aware Knowledge Discovery and Delivery” for the design of the ConQueSt system for the constraint-based discovery of patterns.
01/02/2004 – 10/31/2004: Research Fellow at the I.S.T.I. “A. Faedo” – C.N.R. within the internal project “P3D: Privacy Preserving Pattern Discovery”, for the design and evaluation of novel algorithms for the discovery of frequent patterns, under the supervision of Fosca Giannotti, head of the Knowledge Discovery and Delivery (KDD).

Teaching

Courses:

High Performance Computing (30 hours) at the Dept. of Environmental Sciences, Informatics and Statistics of the Università Ca’ Foscari di Venezia. Topics: distributed- multicore- GPU- programming. (2019)
Web Intelligence (30 hours) at the Dept. of Environmental Sciences, Informatics and Statistics of the Università Ca’ Foscari di Venezia. Topics: supervised and un-supervised methods for data and web mining. (2019)
Highlights in Web Search and Data Mining (10 hours) Ph.D. course “Computer Science” at the Dept. of Environmental Sciences, Informatics and Statistics of the Università Ca’ Foscari di Venezia. (2019)
Lab Of Information Systems And Analytics (30 hours) at the Dept. of Management of the Università Ca’ Foscari di Venezia. Topics: supervised and un-supervised methods for data science. (2019)
Introduction to Coding and Data Management (30 hours) at the Dept. of Management of the Università Ca’ Foscari di Venezia. Topics: problem solving, programming, data management. (2019)
High Performance Computing (48 hours) at the Dept. of Environmental Sciences, Informatics and Statistics of the Università Ca’ Foscari di Venezia. Topics: distributed- multicore- GPU- programming. (2018)
Highlights in Web Search and Data Mining (30 hours) Ph.D. course “Computer Science” at the Dept. of Environmental Sciences, Informatics and Statistics of the Università Ca’ Foscari di Venezia. (2018)
Introduction to Coding and Data Management (60 hours) at the Dept. of Management of the Università Ca’ Foscari di Venezia. Topics: problem solving, programming, data management. (2018)
Data Mining (48 hours) at the Computer Science department of the Università di Firenze. Topics: Association Rules, Clustering, Classiﬁcation, learning to rank, Web mining. (2013, 2015)
Cloud Computing for Big data Analysis (21 hours, in collaboration with F.M. Nardini and N. Tonellotto), Ph.D. course “Information Engineering” at Università di Pisa (2015) and Ph.D. course “Computer, Decision, and Systems Science” at I.M.T. Institute for Advanced Studies Lucca (2014). Topics: cloud computing, large scale data analysis and mining.
High Performance and Scalable Analytics, NO-SQL Big Data Platforms (20 hours, in collaboration with R. Trasarti), Second Level Master on “Big Data Analytics And Social Mining” at Università di Pisa. Topics: Big Data platforms and data analysis algorithms. (2015, 2016, 2017)
Advanced Computer Architectures (48 hours) at the Computer Science department of the Università di Firenze. Topics: distributed- multicore- GPU- programming. (2010, 2011, 2012, 2014, 2016, 2017)
Data Management for Cultural Heritage (21 hours, in collaboration with R. Perego, F. Silvestri until 2013 and S. Orlando from 2014), Ph.D. course “Management and Development of Cultural Heritage” at I.M.T. Institute for Advanced Studies Lucca. Topics: image analysis, tourist proﬁling, data mining. (2012, 2013, 2014, 2015, 2016, 2017)
Web Design Laboratory (48 hours) at the Computer Science in the Humanities department of the Università di Pisa. Topics: PHP and Web 2.0. (February-June 2011)
E-Commerce (48 hours) at the Computer Science department of the Università Ca’ Foscari di Venezia. Topics: Recommender systems and Web advertising. (February-June 2010)
Parallel Programming laboratory (10 hours), funded by the SFIDA project, at the Computer Science of the Università di Pisa. Topics: introduction to parallel programming in Java. (September 2008)
Data Mining (38 hours), funded by the F.S.E. (European Social Fund), at the Computer Science department of the Università Ca’ Foscari di Venezia. Topics: fundamentals of data mining, data mining and the web, the Weka toolkit. (November-December 2007)
Programming (teaching assistant) (30 hours) at the “S.Simoni” secondary school in Lucca. Topics: fundamentals of java programming. (March 2006)
Parallel Programming (teaching assistant) at the Computer Science department of the Università di Pisa. Topics: java message passing and synchronization. (December 2005)
Web Designer (60 hours), funded by the F.S.E. (European Social Fund). Topics: Macromedia Flash design and programming. (Venice, April 2002)

PhD Students:

Seyum Assefa Abebe, Adversarial Machine Learning, Dipartimento di Scienze Ambientali, Informatica e Statistica, Università Ca’ Foscari di Venezia, 2018–.
Mauro Coletto, Social Media Analysis, Computer Science and Engineering, I.M.T. Institute for Advanced Studies Lucca, 2014–2017.
Gianmarco De Francisci Morales, Big Data and the Web: Algorithms for Data Intensive Scalable Computing, co-supervised with R. Baraglia, Computer Science and Engineering, I.M.T. Institute for Advanced Studies Lucca, 2009–2012.

MSc Students:

Alessandro Romano, Deep Learning for anomaly detection in automotive data, co-supervised with R. Venturini and F.M. Nardini, Dept. of Computer Science, Università di Pisa, 2018.
Federico Conte, On optimizing Gradient-Boosted Regression Tree Learning through load-balancing and cache-aware data layout, co-supervised with R. Venturini, Dept. of Computer Science, Università di Pisa, 2016.
Chiara Pierucci, Entity linking and graph analysis for visual summarization of literaty texts, Dept. of Statistics, Computer Science and Applications, Università di Firenze, 2015.
Marco Fascetti, Pruning strategies to improve the eﬃciency of forests of regression trees, Dept. of Statistics, Computer Science and Applications, Università di Firenze, 2015.
Ugo Vespier, Bringing Order to Social Photo Collections: Augmenting and Re-organizing Geotagged Visual Content by Exploiting Social Wisdom, co-supervised with F. Silvestri, Dept. of Computer Science, Università di Pisa, 2010. Franco Denoth Best Thesis Award 2011. Demos: photo clusters and historical clusters.
Ignacio Arnaldo Lucas, Automatic Image Tagging, Facultad de Informática, Departamento de Arquitectura de Computadores y Automática, Universidad Complutense de Madrid, 2010. Best Thesis Award 2010.

BSc Students:

Luca Mion, Optimal Decision Trees, Dipartimento di Scienze Ambientali, Informatica e Statistica, Università Ca’ Foscari di Venezia, 2019.
Roberto Perissa, Spatio-temporal analysis of news, Dipartimento di Scienze Ambientali, Informatica e Statistica, Università Ca’ Foscari di Venezia, 2018.
Jessica Busatto, Trends In News. A news retrieval system for monitoring sentiments over time, Dept. of Computer Science, Università Ca’ Foscari di Venezia, 2011.
Ilieva Rumyana, Creazione semi-automatica di una guida ipertestuale per la Galleria degli Uﬃzi, Dept. of Computer Science in the Humanities, Università di Pisa, 2011.
Simone Torlai, Wine Tour Tuscany, Dept. of Computer Science in the Humanities, Università di Pisa, 2011.
Alessandro Popaiz, Tecniche di clustering applicate ai motori di ricerca web, Dept. of Computer Science, Università Ca’ Foscari di Venezia, 2010.

Apprenticeships:

Samuele Borgheresi, Financial transactions analysis with Apache Spark, LIST Group Pisa, Università di Pisa, 2015.
Michele De Stefano, Raﬀaele Donati, Sviluppo di una applicazione per l’annotazione automatica di testi, IIS “E. Fermi - Giorgi”, Lucca, 2014.
Lorenzo Berti, Sviluppo di una applicazione Web per l’annotazione e la valutazione manuale di dati per sistemi informatici di apprendimento automatico, Dept. of Computer Science in the Humanities, Università di Pisa, 2012.
Marco Bellio, Stefano Cappellini, Sviluppo di una applicazione Web per l’analisi e la visualizzazione di dati con annotazioni spazio-temporali, Dept. of Computer Science in the Humanities, Università di Pisa, 2011.

Participations to national and international projects

SoBigData: Social Mining & Big Data Ecosystem. Supported by the European Community H2020 Program under the scheme INFRAIA-1-2014-2015: Research Infrastructures, grant agreement #654024, http://www.sobigdata.eu. (2014-2018)
- Task leader: “T9.7 Engineering Massive Scale Social Mining”
InGeoCloudS: INspired GEOdata CLOUD Services. Competitiveness and Innovation (CIP) funded by EU. (2012-2014)
- Work Package leader: “WP3: InGeoCloudS Infrastructure”
ASSETS: Advanced Search Service and Enhanced Technological Solutions for the Europeana Digital Library. Best Practice Network funded by EU. (2010-2012)
- Task leader: “T2.2.1 Post Querying Processing”
- Task leader: “T2.2.3 Text Indexing and Retrieval”
VISITO: VIsual Support to Interactive TOurism in Tuscany. National project funded by the region of Tuscany. (2009-2011)
- Work Package leader: “WP6: Scalable and eﬃcient content management”
- Task responsible: “A6.2: Image feature extraction”
SAPIR: Search on Audio-visual content using Peer-to-peer Information Retrieval. STREP IST FP6 Project funded by EU. (2009-2011)
GeoPKDD: Geographic Privacy-aware Knowledge Discovery and Delivery. National project funded by PRIN Italy. (2007-2009)
P3D: Privacy Preserving Pattern Discovery. Curiosity Driven Project funded by I.S.T.I. “A. Faedo” – C.N.R.. (2004)

References

[1] Mario Boley, Claudio Lucchese, Daniel Paurat, and Thomas Gärtner. Direct local pattern sampling by eﬃcient two-step random procedures. In KDD ’11: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 582–590, August 21-24 2011.

[2] Diego Ceccarelli, Claudio Lucchese, Salvatore Orlando, Raﬀaele Perego, and Salvatore Trani. SEL: a uniﬁed algorithm for entity linking and saliency detection. In DocEng ’16: Proceedings of the 2015 ACM Symposium on Document Engineering, 2016.

[3] Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raﬀaele Perego, Nicola Tonellotto, and Rossano Venturini. Quickscorer: a fast algorithm to rank documents with additive ensembles of regression trees. In SIGIR ’15: Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2015. (best paper) (ACM Notable Article).

[4] Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raﬀaele Perego, and Salvatore Trani. Selective gradient boosting for eﬀective learning to rank. In SIGIR ’18: Proceedings of the 41th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2018.

[5] Claudio Lucchese, Salvatore Orlando, and Raﬀaele Perego. Fast and memory eﬃcient mining of frequent closed itemsets. IEEE Transactions On Knowledge and Data Engineering, 18(1):21–36, 2006.

[6] Claudio Lucchese, Salvatore Orlando, and Raﬀaele Perego. A unifying framework for mining approximate top-k binary patterns. IEEE Transactions On Knowledge and Data Engineering, 26(12):2900–2913, 2014.

[7] Claudio Lucchese, Salvatore Orlando, Raﬀaele Perego, Fabrizio Silvestri, and Gabriele Tolomei. Discovering tasks from search engine query logs. ACM Trans. Inf. Syst., 31(3):14, 2013. (ACM Notable Article).

[8] Claudio Lucchese, Deepak Rayan, Michalis Vlachos, and Philip S. Yu. Rights protection of trajectory datasets with nearest-neighbor preservation. VLDB Journal, 19(4):531–556, 2010.

[9] Alessandro Lulli, Emanuele Carlini, Patrizio Dazzi, Claudio Lucchese, and Laura Ricci. Fast connected components computation in large graphs by vertex pruning. IEEE Transactions on Parallel and Distributed Systems, 28(3):760–773, 2017.

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Claudio Lucchese