Violetta Lonati

821 total citations
45 papers, 318 citations indexed

About

Violetta Lonati is a scholar working on Computer Science Applications, Developmental and Educational Psychology and Artificial Intelligence. According to data from OpenAlex, Violetta Lonati has authored 45 papers receiving a total of 318 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Computer Science Applications, 12 papers in Developmental and Educational Psychology and 11 papers in Artificial Intelligence. Recurrent topics in Violetta Lonati's work include Teaching and Learning Programming (25 papers), semigroups and automata theory (8 papers) and Educational Games and Gamification (8 papers). Violetta Lonati is often cited by papers focused on Teaching and Learning Programming (25 papers), semigroups and automata theory (8 papers) and Educational Games and Gamification (8 papers). Violetta Lonati collaborates with scholars based in Italy, United States and Finland. Violetta Lonati's co-authors include Mattia Monga, Crispino Tosto, Giuseppe Chiazzese, Marco Arrigo, Dario Malchiodi, Massimiliano Goldwurm, Carlo Bellettini, Cruz Izu, Claudio Mirolo and Alberto Bertoni and has published in prestigious journals such as SIAM Journal on Computing, Theoretical Computer Science and Information and Computation.

In The Last Decade

Violetta Lonati

43 papers receiving 298 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Violetta Lonati Italy	9	214	74	73	73	49	45	318
Aidan Mooney Ireland	11	246 1.1×	53 0.7×	54 0.7×	86 1.2×	30 0.6×	40	388
Samiha Marwan United States	11	280 1.3×	84 1.1×	128 1.8×	147 2.0×	30 0.6×	26	370
Dennis Brylow United States	11	154 0.7×	59 0.8×	47 0.6×	44 0.6×	56 1.1×	47	336
Tom Naps United States	10	273 1.3×	84 1.1×	61 0.8×	136 1.9×	51 1.0×	17	381
Monika Akbar United States	8	174 0.8×	97 1.3×	52 0.7×	94 1.3×	40 0.8×	33	345
Michael T. Grinder United States	11	153 0.7×	27 0.4×	77 1.1×	66 0.9×	54 1.1×	16	282
Viraj Kumar India	8	201 0.9×	116 1.6×	141 1.9×	30 0.4×	60 1.2×	45	397
Doug Baldwin United States	13	282 1.3×	124 1.7×	82 1.1×	101 1.4×	50 1.0×	54	420
Barbara Demo Italy	4	236 1.1×	62 0.8×	45 0.6×	99 1.4×	21 0.4×	7	295
Marja Kuittinen Finland	11	368 1.7×	132 1.8×	80 1.1×	197 2.7×	95 1.9×	22	439

Countries citing papers authored by Violetta Lonati

Since Specialization

Citations

This map shows the geographic impact of Violetta Lonati'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 Violetta Lonati with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Violetta Lonati more than expected).

Fields of papers citing papers by Violetta Lonati

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Violetta Lonati. 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 Violetta Lonati. The network helps show where Violetta Lonati may publish in the future.

Co-authorship network of co-authors of Violetta Lonati

This figure shows the co-authorship network connecting the top 25 collaborators of Violetta Lonati. A scholar is included among the top collaborators of Violetta Lonati 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 Violetta Lonati. Violetta Lonati is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Lonati, Violetta, et al.. (2025). A Pedagogical Framework for Developing Abstraction Skills. Durham Research Online (Durham University). 258–299. 1 indexed citations

Barendsen, Erik, Violetta Lonati, Keith Quille, et al.. (2024). AI in and for K-12 Informatics Education. Life after Generative AI.. VTechWorks (Virginia Tech). 279–280. 2 indexed citations

Bellettini, Carlo, et al.. (2024). To Be Or Not To Be . . . An Algorithm: The Notion According to Students and Teachers. Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano). 102–108. 1 indexed citations

Bellettini, Carlo, et al.. (2023). Davinci Goes to Bebras: A Study on the Problem Solving Ability of GPT-3. SPIRE - Sciences Po Institutional REpository. 59–69. 6 indexed citations

Capecchi, Sara, et al.. (2023). Castle and Stairs to Learn Iteration: Co-designing a UMC Learning Module with Teachers. SPIRE - Sciences Po Institutional REpository. 222–228. 2 indexed citations

Korhonen, Ari, et al.. (2023). Empirical Evaluation of a Differentiated Assessment of Data Structures: The Role of Prerequisite Skills. Informatics in Education.

Nardelli, Enrico, Renzo Davoli, Michael Lodi, et al.. (2022). Learning Iteration for Grades 2-3. Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano). 1368–1368. 1 indexed citations

Mirolo, Claudio, et al.. (2021). Abstraction in Computer Science Education: An Overview. Informatics in Education. 20(4). 615–639. 8 indexed citations

Nelson, Greg L., et al.. (2020). Differentiated Assessments for Advanced Courses that Reveal Issues with Prerequisite Skills. CBS Research Portal (Copenhagen Business School). 75–129. 9 indexed citations

10.

Bellettini, Carlo, et al.. (2019). An Analysis of the Performance of Italian Schools in Bebras and in the National Student Assessment INVALSI. 2434. 1–12. 1 indexed citations

11.

Lonati, Violetta, et al.. (2016). A playful tool to introduce lower secondary school pupils to recursive thinking. 51–52. 2 indexed citations

12.

Reghizzi, Stefano Crespi, Violetta Lonati, Dino Mandrioli, & Matteo Pradella. (2016). Toward a theory of input-driven locally parsable languages. Theoretical Computer Science. 658. 105–121. 3 indexed citations

13.

Lonati, Violetta & Matteo Pradella. (2010). Deterministic recognizability of picture languages with Wang automata. Discrete Mathematics & Theoretical Computer Science. Vol. 12 no. 4. 2 indexed citations

14.

Bertoni, Alberto, Massimiliano Goldwurm, & Violetta Lonati. (2009). The Complexity of Unary Tiling Recognizable Picture Languages: Nondeterministic and Unambiguous Cases. Fundamenta Informaticae. 91(2). 231–249. 5 indexed citations

15.

Lonati, Violetta, et al.. (2008). Working for a leap in the general perception of computing. 134–139. 4 indexed citations

16.

Boldi, Paolo, et al.. (2008). The number of convex permutominoes. Information and Computation. 206(9-10). 1074–1083. 4 indexed citations

17.

Boldi, Paolo, Violetta Lonati, Massimo Santini, & Sebastiano Vigna. (2006). Graph fibrations, graph isomorphism, and PageRank. RAIRO - Theoretical Informatics and Applications. 40(2). 227–253. 17 indexed citations

18.

Goldwurm, Massimiliano, et al.. (2004). Frequency of symbol occurrences in bicomponent stochastic models. Theoretical Computer Science. 327(3). 269–300. 5 indexed citations

19.

Bertoni, Alberto, Christian Choffrut, Massimiliano Goldwurm, & Violetta Lonati. (2003). On the number of occurrences of a symbol in words of regular languages. Theoretical Computer Science. 302(1-3). 431–456. 22 indexed citations

20.

Lonati, Violetta, et al.. (2003). On the number of occurrences of a symbol in words of regular languages. HAL (Le Centre pour la Communication Scientifique Directe). 2 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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