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个人简介
Nicola Tonellotto was born in La Spezia, Italy, on October 20th, 1975. He graduated in Computer Engineering (spec. industrial automation and robotics), Summa Cum Laude, in 2002 from the University of Pisa. He received a PhD in Information Engineering (supervised by Dr. Domenico Laforenza) from the University of Pisa and a PhD in Computer Engineering from the University of Dortmund (supervised by Prof. Dr.-Ing. Uwe Schwiegelshohn) both in 2008.
From 2002 to 2006 he has been a research fellow at the Information Science and Technologies Institute of the Italian National Research Council. Since 2007 he is afull researcher at the same institute. His main research interests include grid computing, cloud computing, resource management and Web information retrieval. Nicola Tonellotto co-authored more than 30 papers on these topics in peer reviewed international journal and conferences. He also contributed to design and implement several software tools, such as the ASSIST programming environment and runtime support, the Grid Network Resource Broker, the Grid Execution Agent, the Grid Component Model reference implementation and the open source search engine TERRIER. He participated and coordinated activities in several EC projects such as CoreGRID, NextGRID, GRIDComp, S-Cube and InGeoClouds. Since 2009 he teaches the course “Distributed Enabling Platforms” at the Department of Computer Science of the University of Pisa.
研究兴趣
论文共 153 篇作者统计合作学者相似作者
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ACM TRANSACTIONS ON INFORMATION SYSTEMSno. 2 (2024): 61:1-61:35
Lecture Notes in Computer Science Advances in Information Retrievalpp.111-125, (2024)
Florin Cuconasu,Giovanni Trappolini,Federico Siciliano, Simone Filice,Cesare Campagnano, Yoelle Maarek,Nicola Tonellotto,Fabrizio Silvestri
CoRR (2024)
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CoRR (2023): 1-5
CoRR (2023): 29-37
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Comput. Commun. (2023): 0-12
PROCEEDINGS OF THE 46TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, SIGIR 2023pp.1355-1365, (2023)
ACM Trans. Webno. 1 (2023): 3:1-3:39
SIGIR Forumno. 2 (2023): 8:1-8:12
PROCEEDINGS OF THE 17TH ACM CONFERENCE ON RECOMMENDER SYSTEMS, RECSYS 2023 (2023): 1114-1119
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