Pier Luca Lanzi

6.9k total citations
176 papers, 3.8k citations indexed

About

Pier Luca Lanzi is a scholar working on Artificial Intelligence, Molecular Biology and Information Systems. According to data from OpenAlex, Pier Luca Lanzi has authored 176 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 120 papers in Artificial Intelligence, 32 papers in Molecular Biology and 22 papers in Information Systems. Recurrent topics in Pier Luca Lanzi's work include Evolutionary Algorithms and Applications (94 papers), Metaheuristic Optimization Algorithms Research (63 papers) and Artificial Intelligence in Games (28 papers). Pier Luca Lanzi is often cited by papers focused on Evolutionary Algorithms and Applications (94 papers), Metaheuristic Optimization Algorithms Research (63 papers) and Artificial Intelligence in Games (28 papers). Pier Luca Lanzi collaborates with scholars based in Italy, United States and United Kingdom. Pier Luca Lanzi's co-authors include Daniele Loiacono, Stewart W. Wilson, Luigi Cardamone, Martin V. Butz, Federico Michele Facca, David E. Goldberg, Michele Pirovano, N. Alberto Borghese, Wolfgang Stolzmann and Renato Mainetti and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Pier Luca Lanzi

173 papers receiving 3.6k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Pier Luca Lanzi Italy 35 2.5k 755 451 387 371 176 3.8k
David Bell United Kingdom 26 1.7k 0.7× 159 0.2× 811 1.8× 347 0.9× 435 1.2× 200 3.3k
Giovanni Acampora Italy 27 1.3k 0.5× 138 0.2× 448 1.0× 475 1.2× 557 1.5× 177 2.5k
Salvatore Gaglio Italy 24 928 0.4× 152 0.2× 209 0.5× 457 1.2× 595 1.6× 193 2.2k
Philip Hingston Australia 21 2.3k 0.9× 38 0.1× 139 0.3× 222 0.6× 201 0.5× 71 3.5k
Wenbing Zhao United States 29 690 0.3× 45 0.1× 858 1.9× 1.2k 3.2× 614 1.7× 212 3.2k
Ah‐Hwee Tan Singapore 30 2.3k 0.9× 168 0.2× 548 1.2× 273 0.7× 1.1k 2.8× 219 3.9k
Paul S. Rosenbloom United States 25 2.9k 1.2× 73 0.1× 282 0.6× 408 1.1× 257 0.7× 113 4.1k
M. Shamim Hossain Saudi Arabia 35 815 0.3× 35 0.0× 837 1.9× 1.3k 3.4× 836 2.3× 100 3.4k
Sandeep Subramanian Canada 19 2.6k 1.0× 413 0.5× 330 0.7× 61 0.2× 348 0.9× 59 4.0k
John E. Laird United States 34 4.6k 1.8× 66 0.1× 318 0.7× 479 1.2× 595 1.6× 178 6.1k

Countries citing papers authored by Pier Luca Lanzi

Since Specialization
Citations

This map shows the geographic impact of Pier Luca Lanzi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Pier Luca Lanzi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pier Luca Lanzi more than expected).

Fields of papers citing papers by Pier Luca Lanzi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pier Luca Lanzi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Pier Luca Lanzi. The network helps show where Pier Luca Lanzi may publish in the future.

Co-authorship network of co-authors of Pier Luca Lanzi

This figure shows the co-authorship network connecting the top 25 collaborators of Pier Luca Lanzi. A scholar is included among the top collaborators of Pier Luca Lanzi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pier Luca Lanzi. Pier Luca Lanzi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Gozzi, Noemi, Martina Sollini, Margarita Kirienko, et al.. (2022). Image Embeddings Extracted from CNNs Outperform Other Transfer Learning Approaches in Classification of Chest Radiographs. Diagnostics. 12(9). 2084–2084. 7 indexed citations
2.
Lanzi, Pier Luca, et al.. (2021). Image Embedding and Model Ensembling for Automated Chest X-Ray Interpretation. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 3 indexed citations
3.
Borghese, N. Alberto, et al.. (2013). Computational Intelligence and Game Design for Effective At-Home Stroke Rehabilitation. Games for Health Journal. 2(2). 81–88. 68 indexed citations
4.
Pirovano, Michele, Renato Mainetti, Gabriel Baud‐Bovy, Pier Luca Lanzi, & N. Alberto Borghese. (2012). Self-adaptive games for rehabilitation at home. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 179–186. 80 indexed citations
5.
Krasnogor, Natalio & Pier Luca Lanzi. (2011). Proceedings of the 13th annual conference on Genetic and evolutionary computation. Genetic and Evolutionary Computation Conference. 6 indexed citations
6.
Tumeo, Antonino, Christian Pilato, Fabrizio Ferrandi, Donatella Sciuto, & Pier Luca Lanzi. (2008). Ant colony optimization for mapping and scheduling in heterogeneous multiprocessor systems. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 142–149. 25 indexed citations
7.
Kovacs, Tim, et al.. (2007). Learning Classifier Systems, International Workshops, IWLCS 2003-2005, Revised Selected Papers. DIAL (Catholic University of Leuven). 4 indexed citations
8.
Meo, Rosa, Pier Luca Lanzi, & Mika Klemettinen. (2004). Database Support for Data Mining Applications: Discovering Knowledge with Inductive Queries (Lecture Notes in Computer Science). Springer eBooks. 3 indexed citations
9.
Lanzi, Pier Luca, et al.. (2002). Advances in learning classifier systems : 4th International Workshop, IWLCS 2001, San Francisco, CA, USA, July 7-8, 2001 : revised papers. Springer eBooks. 3 indexed citations
10.
Butz, Martin V., Tim Kovacs, Pier Luca Lanzi, & Stewart W. Wilson. (2001). How XCS evolves accurate classifiers. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 927–934. 34 indexed citations
11.
Miller, Julian F., Marco Tomassini, Pier Luca Lanzi, et al.. (2001). Genetic programming : 4th European conference, EuroGP 2001, Lake Como, Italy, April 18-20, 2001 : proceedings. Springer eBooks.
12.
Lanzi, Pier Luca, et al.. (2001). Advances in learning classifier systems : Third International Workshop, IWLCS 2000, Paris, France, September 15-16, 2000 : revised papers. Springer eBooks. 5 indexed citations
13.
Lanzi, Pier Luca. (2001). Mining interesting knowledge from data with the XCS classifier system. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 958–965. 15 indexed citations
14.
Lanzi, Pier Luca. (2000). Adaptive Agents with Reinforcement Learning and Internal Memory. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 23(1). 333–342. 24 indexed citations
15.
Lanzi, Pier Luca & Marco Colombetti. (1999). An extension to the XCS classifier system for stochastic environments. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 353–360. 22 indexed citations
16.
Lanzi, Pier Luca & Giuseppe Psaila. (1999). A Relational Database Mining Framework with Classification and Discretization.. SEBD. 101–115. 1 indexed citations
17.
Lanzi, Pier Luca. (1999). Extending the representation of classifier conditions part I: from binary to messy coding. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 337–344. 41 indexed citations
18.
Lanzi, Pier Luca, et al.. (1999). Extending the Representation of Classifier Conditions Part II: From Messy Coding to S-Expressions. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 345–352. 72 indexed citations
19.
Lanzi, Pier Luca. (1998). An Analysis of the Memory Mechanism of XCSM. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 13 indexed citations
20.
Lanzi, Pier Luca, et al.. (1996). Performing effective feature selection by investigating the deep structure of the data. OpenGrey (Institut de l'Information Scientifique et Technique). 379–382. 17 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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