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Computer Science
Italy
2025

D-Index & Metrics

Computer Science

D-Index
56
Citations
8985
World Ranking
4160
National Ranking
86

Research.com Recognitions

  • 2025 - Research.com Computer Science in Italy Leader Award
  • 2023 - Research.com Computer Science in Italy Leader Award
  • 2022 - Research.com Computer Science in Italy Leader Award

Overview

Pier Luca Lanzi is affiliated with the Polytechnic University of Milan in Italy. Their research spans multiple disciplines within computer science and medicine, focusing in particular on applications of artificial intelligence and virtual reality.

The scientist's main fields of study include:

  • Computer Science
  • Medicine

Within these broader fields, their subfields of study encompass:

  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Developmental and Educational Psychology

The primary research topics covered by their work include:

  • Artificial Intelligence in Games
  • Virtual Reality Applications and Impacts
  • Radiomics and Machine Learning in Medical Imaging
  • Educational Games and Gamification
  • COVID-19 diagnosis using AI
  • Digital Games and Media
  • Evolutionary Algorithms and Applications

The scientist's recent papers illustrate these topics and fields in practice, including:

  • ChatGPT and Other Large Language Models as Evolutionary Engines for Online Interactive Collaborative Game Design (2023) published in Proceedings of the Genetic and Evolutionary Computation Conference
  • Distributed learning: a reliable privacy-preserving strategy to change multicenter collaborations using AI (2021) published in European Journal of Nuclear Medicine and Molecular Imaging
  • An educational experience in ancient Rome to evaluate the impact of virtual reality on human learning processes (2023) published in Computers & Education X Reality
  • A virtual reality classroom to teach and explore crystal solid state structures (2022) published in Multimedia Tools and Applications
  • Image Embeddings Extracted from CNNs Outperform Other Transfer Learning Approaches in Classification of Chest Radiographs (2022) published in Diagnostics

The scientist frequently collaborates with several co-authors, including:

  • Daniele Loiacono
  • Edoardo Giacomello
  • Paolo Boffi
  • M. Clerici
  • Alberto Gallace

Their publications are disseminated in a range of venues with multiple works appearing in:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Proceedings of the Genetic and Evolutionary Computation Conference
  • European Journal of Nuclear Medicine and Molecular Imaging
  • Computers & Education X Reality

Best Publications

  • Mining interesting knowledge from weblogs: a survey

    Federico Michele Facca;Pier Luca Lanzi

  • An analysis of generalization in the xcs classifier system

    Pier Luca Lanzi

  • Toward a theory of generalization and learning in XCS

    M.V. Butz;T. Kovacs;P.L. Lanzi;S.W. Wilson

  • Architectures for an Event Notification Service Scalable to Wide-area Networks

    Antonio Carzaniga;Luciano Baresi;Gino Biondini;Fabiano Cattaneo

  • Learning Classifier Systems, From Foundations to Applications

    Pier Luca Lanzi;Wolfgang Stolzmann;Stewart W. Wilson

  • Learning Classifier Systems

    Larry Bull;Pier Luca Lanzi;Wolfgang Stolzmann

  • Ant Colony Heuristic for Mapping and Scheduling Tasks and Communications on Heterogeneous Embedded Systems

    Fabrizio Ferrandi;Pier Luca Lanzi;Christian Pilato;Donatella Sciuto

  • Exergaming and rehabilitation: A methodology for the design of effective and safe therapeutic exergames

    Michele Pirovano;Elif Surer;Renato Mainetti;Pier Luca Lanzi

  • Extending the representation of classifier conditions part I: from binary to messy coding

    Pier Luca Lanzi

  • Procedural Content Generation: Goals, Challenges and Actionable Steps

    Julian Togelius;Alex J. Champandard;Pier Luca Lanzi;Michael Mateas

  • What Is a Learning Classifier System

    John H. Holland;Lashon B. Booker;Marco Colombetti;Marco Dorigo

  • Fast feature selection with genetic algorithms: a filter approach

    P.L. Lanzi

  • Self-adaptive games for rehabilitation at home

    Michele Pirovano;Renato Mainetti;Gabriel Baud-Bovy;Pier Luca Lanzi

  • Function Approximation With XCS: Hyperellipsoidal Conditions, Recursive Least Squares, and Compaction

    M.V. Butz;P.L. Lanzi;S.W. Wilson

  • Computational Intelligence and Game Design for Effective At-Home Stroke Rehabilitation

    Nunzio Alberto Borghese;Michele Pirovano;Pier Luca Lanzi;Seline Wüest

  • Learning classifier systems: New models, successful applications

    John H. Holmes;Pier Luca Lanzi;Wolfgang Stolzmann;Stewart W. Wilson

  • The 2009 Simulated Car Racing Championship

    Daniele Loiacono;Pier Luca Lanzi;Julian Togelius;Enrique Onieva

  • Toward Optimal Classifier System Performance in Non-Markov Environments

    Pier Luca Lanzi;Stewart W. Wilson

  • Gradient descent methods in learning classifier systems: improving XCS performance in multistep problems

    M.V. Butz;D.E. Goldberg;P.L. Lanzi

  • Learning classifier systems: then and now

    Pier Luca Lanzi

  • Advances in Learning Classifier Systems

    Unknown

  • Genetic and Evolutionary Computation – GECCO 2004

    Unknown

Frequent Co-Authors

Stewart W. Wilson
Stewart W. Wilson University of Illinois at Urbana-Champaign
David E. Goldberg
David E. Goldberg University of Illinois at Urbana-Champaign
Martin V. Butz
Martin V. Butz University of Tübingen
Donatella Sciuto
Donatella Sciuto Polytechnic University of Milan
Larry Bull
Larry Bull University of the West of England
Kumara Sastry
Kumara Sastry University of Illinois at Urbana-Champaign
Stefano Ceri
Stefano Ceri Polytechnic University of Milan
Julian Togelius
Julian Togelius New York University
N. Alberto Borghese
N. Alberto Borghese University of Milan
Luciano Baresi
Luciano Baresi Polytechnic University of Milan

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