World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
5005
World Ranking
10374
National Ranking
314

Overview

Salvatore Orlando is affiliated with Ca Foscari University of Venice in Italy and has contributed extensively to the field of Computer Science, with a focus on several specialized subfields and topics.

The main areas of study for Orlando include:

  • Artificial Intelligence
  • Safety Research
  • Management Science and Operations Research
  • Signal Processing
  • Information Systems

The primary research topics covered in Orlando's work consist of:

  • Adversarial Robustness in Machine Learning
  • Explainable Artificial Intelligence (XAI)
  • Anomaly Detection Techniques and Applications
  • Ethics and Social Impacts of AI
  • Advanced Malware Detection Techniques
  • Data Quality and Management
  • Machine Learning and Data Classification

Salvatore Orlando has published several papers, notable examples include:

  • "Treant: training evasion-aware decision trees", 2020, Data Mining and Knowledge Discovery
  • "Treant: training evasion-aware decision trees", 2020, IRIS Research product catalog (Sapienza University of Rome)
  • "Comparison of the impact of ships to size-segregated particle concentrations in two harbour cities of northern Adriatic Sea", 2020, Environmental Pollution
  • "Beyond robustness: Resilience verification of tree-based classifiers", 2022, Computers & Security
  • "Feature partitioning for robust tree ensembles and their certification in adversarial scenarios", 2021, EURASIP Journal on Information Security

The frequent publication venues where their research appears include:

  • arXiv (Cornell University)
  • IRIS Research product catalog (Sapienza University of Rome)
  • Environmental Pollution
  • Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing
  • Computers & Security

Frequent collaborators in Orlando's research efforts comprise:

  • Claudio Lucchese
  • Stefano Calzavara
  • Federico Marcuzzi
  • Franco Maria Nardini
  • Raffaele Perego

Salvatore Orlando's publications have contributed knowledge related to the resilience and robustness of machine learning models, especially in the context of adversarial scenarios and explainability, intersecting with broader concerns on ethics and social impacts of artificial intelligence.

Best Publications

  • Fast and memory efficient mining of frequent closed itemsets

    C. Lucchese;S. Orlando;R. Perego

  • P3L: a Structured High-level Parallel Language and its Structured Support

    Bruno Bacci;Marco Danelutto;Salvatore Orlando;Susanna Pelagatti

  • Boosting the performance of Web search engines: Caching and prefetching query results by exploiting historical usage data

    Tiziano Fagni;Raffaele Perego;Fabrizio Silvestri;Salvatore Orlando

  • Enhancing the Apriori Algorithm for Frequent Set Counting

    Salvatore Orlando;Paolo Palmerini;Raffaele Perego

  • Identifying task-based sessions in search engine query logs

    Claudio Lucchese;Salvatore Orlando;Raffaele Perego;Fabrizio Silvestri

  • Adaptive and resource-aware mining of frequent sets

    S. Orlando;P. Palmerini;R. Perego;F. Silvestri

  • A methodology for the development and the support of massively parallel programs

    Marco Danelutto;Marco Danelutto;Robert Di Meglio;Salvatore Orlando;Salvatore Orlando;Susanna Pelagatti

  • Learning relatedness measures for entity linking

    Diego Ceccarelli;Claudio Lucchese;Salvatore Orlando;Raffaele Perego

  • kDCI: a Multi-Strategy Algorithm for Mining Frequent Sets.

    Salvatore Orlando;Claudio Lucchese;Paolo Palmerini;Raffaele Perego

  • Trajectory Data Warehouses: Design and Implementation Issues

    Salvatore Orlando;Renzo Orsini;Alessandra Raffaetà;Alessandro Roncato

  • Fast Ranking with Additive Ensembles of Oblivious and Non-Oblivious Regression Trees

    Domenico Dato;Claudio Lucchese;Franco Maria Nardini;Salvatore Orlando

  • Dexter: an open source framework for entity linking

    Diego Ceccarelli;Claudio Lucchese;Salvatore Orlando;Raffaele Perego

  • QuickScorer: A Fast Algorithm to Rank Documents with Additive Ensembles of Regression Trees

    Claudio Lucchese;Franco Maria Nardini;Salvatore Orlando;Raffaele Perego

  • A new algorithm for gap constrained sequence mining

    Salvatore Orlando;Raffaele Perego;Claudio Silvestri

  • Peer-to-peer systems for discovering resources in a dynamic grid

    Moreno Marzolla;Matteo Mordacchini;Salvatore Orlando

  • Discovering tasks from search engine query logs

    Claudio Lucchese;Salvatore Orlando;Raffaele Perego;Fabrizio Silvestri

  • DCI_Closed: A Fast and Memory Efficient Algorithm to Mine Frequent Closed Itemsets

    Claudio Lucchese;Salvatore Orlando;R. Perego

  • Assigning identifiers to documents to enhance the clustering property of fulltext indexes

    Fabrizio Silvestri;Salvatore Orlando;Raffaele Perego

  • Quality versus efficiency in document scoring with learning-to-rank models

    Gabriele Capannini;Claudio Lucchese;Franco Maria Nardini;Salvatore Orlando

  • Mining Top-K Patterns from Binary Datasets in presence of Noise

    Claudio Lucchese;Salvatore Orlando;Raffaele Perego

  • DCI Closed: A Fast and Memory Efficient Algorithm to Mine Frequent Closed Itemsets.

    Claudio Lucchese;Salvatore Orlando;Raffaele Perego

Frequent Co-Authors

Raffaele Perego
Raffaele Perego Institute of Information Science and Technologies
Claudio Lucchese
Claudio Lucchese Ca Foscari University of Venice
Fabrizio Silvestri
Fabrizio Silvestri Sapienza University of Rome
Domenico Talia
Domenico Talia University of Calabria
Christian S. Jensen
Christian S. Jensen Aalborg University
Francesco Bonchi
Francesco Bonchi Institute for Scientific Interchange
Fosca Giannotti
Fosca Giannotti Scuola Normale Superiore di Pisa
Natalia Andrienko
Natalia Andrienko Fraunhofer Institute for Intelligent Analysis and Information Systems
Iadh Ounis
Iadh Ounis University of Glasgow
Gennady Andrienko
Gennady Andrienko Fraunhofer Institute for Intelligent Analysis and Information Systems

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