Jurica Levatić

446 total citations
16 papers, 265 citations indexed

About

Jurica Levatić is a scholar working on Artificial Intelligence, Molecular Biology and Computational Theory and Mathematics. According to data from OpenAlex, Jurica Levatić has authored 16 papers receiving a total of 265 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 4 papers in Molecular Biology and 4 papers in Computational Theory and Mathematics. Recurrent topics in Jurica Levatić's work include Machine Learning and Data Classification (4 papers), Computational Drug Discovery Methods (3 papers) and Text and Document Classification Technologies (3 papers). Jurica Levatić is often cited by papers focused on Machine Learning and Data Classification (4 papers), Computational Drug Discovery Methods (3 papers) and Text and Document Classification Technologies (3 papers). Jurica Levatić collaborates with scholars based in Slovenia, Italy and Spain. Jurica Levatić's co-authors include Sašo Džeroski, Dragi Kocev, Michelangelo Ceci, Fran Supek, Tomislav Šmuc, Marijeta Kralj, Jasna Ćurak, Maja Osmak, Matej Petković and Marko Debeljak and has published in prestigious journals such as Journal of Medicinal Chemistry, Expert Systems with Applications and Information Sciences.

In The Last Decade

Jurica Levatić

16 papers receiving 258 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jurica Levatić Slovenia 9 139 51 44 38 24 16 265
Shrooq Alsenan Saudi Arabia 9 63 0.5× 45 0.9× 63 1.4× 37 1.0× 14 0.6× 26 230
Zhaoxian Zhou United States 9 95 0.7× 95 1.9× 135 3.1× 73 1.9× 9 0.4× 35 416
Robert Stanforth United Kingdom 9 255 1.8× 31 0.6× 43 1.0× 52 1.4× 10 0.4× 12 333
Hosney Jahan China 10 48 0.3× 94 1.8× 100 2.3× 16 0.4× 45 1.9× 18 271
Wael A. Awad Egypt 8 135 1.0× 18 0.4× 13 0.3× 47 1.2× 111 4.6× 37 320
Nabeela Kausar Pakistan 9 144 1.0× 43 0.8× 12 0.3× 82 2.2× 23 1.0× 19 318
Jian Jiang China 11 45 0.3× 68 1.3× 93 2.1× 23 0.6× 12 0.5× 35 280
Fang Wei Austria 10 109 0.8× 31 0.6× 75 1.7× 57 1.5× 29 1.2× 25 334

Countries citing papers authored by Jurica Levatić

Since Specialization
Citations

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

Fields of papers citing papers by Jurica Levatić

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jurica Levatić

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

All Works

16 of 16 papers shown
1.
Petković, Matej, et al.. (2023). CLUSplus: A decision tree-based framework for predicting structured outputs. SoftwareX. 24. 101526–101526. 5 indexed citations
2.
Petković, Matej, Jurica Levatić, Panče Panov, et al.. (2022). Machine-learning ready data on the thermal power consumption of the Mars Express Spacecraft. Scientific Data. 9(1). 229–229. 5 indexed citations
3.
Levatić, Jurica. (2022). Semi-supervised learning for structured output prediction. Informatica. 46(4). 2 indexed citations
4.
Levatić, Jurica, et al.. (2020). Semi-supervised regression trees with application to QSAR modelling. Expert Systems with Applications. 158. 113569–113569. 16 indexed citations
5.
6.
Petković, Matej, Nikola Simidjievski, Sašo Džeroski, et al.. (2019). Machine Learning for Predicting Thermal Power Consumption of the Mars Express Spacecraft. IEEE Aerospace and Electronic Systems Magazine. 34(7). 46–60. 13 indexed citations
7.
Levatić, Jurica, Ivana Perković, Lidija Uzelac, et al.. (2018). Machine learning prioritizes synthesis of primaquine ureidoamides with high antimalarial activity and attenuated cytotoxicity. European Journal of Medicinal Chemistry. 146. 651–667. 10 indexed citations
8.
Levatić, Jurica, Dragi Kocev, Michelangelo Ceci, & Sašo Džeroski. (2018). Semi-supervised trees for multi-target regression. Information Sciences. 450. 109–127. 36 indexed citations
9.
Levatić, Jurica, et al.. (2017). QSAR based synthesis of novel primaquine ureidoamides. 200. 1 indexed citations
10.
Levatić, Jurica, Michelangelo Ceci, Dragi Kocev, & Sašo Džeroski. (2017). Self-training for multi-target regression with tree ensembles. Knowledge-Based Systems. 123. 41–60. 49 indexed citations
11.
Levatić, Jurica, Michelangelo Ceci, Dragi Kocev, & Sašo Džeroski. (2017). Semi-supervised classification trees. Journal of Intelligent Information Systems. 49(3). 461–486. 31 indexed citations
12.
Kocev, Dragi, et al.. (2017). Predicting Thermal Power Consumption of the Mars Express Satellite with Machine Learning. 88–93. 4 indexed citations
13.
Levatić, Jurica, Dragi Kocev, Marko Debeljak, & Sašo Džeroski. (2014). Community structure models are improved by exploiting taxonomic rank with predictive clustering trees. Ecological Modelling. 306. 294–304. 8 indexed citations
14.
Levatić, Jurica, Dragi Kocev, & Sašo Džeroski. (2014). The importance of the label hierarchy in hierarchical multi-label classification. Journal of Intelligent Information Systems. 45(2). 247–271. 23 indexed citations
15.
Levatić, Jurica, Jasna Ćurak, Marijeta Kralj, et al.. (2013). Accurate Models for P-gp Drug Recognition Induced from a Cancer Cell Line Cytotoxicity Screen. Journal of Medicinal Chemistry. 56(14). 5691–5708. 43 indexed citations
16.
Levatić, Jurica, Sašo Džeroski, Fran Supek, & Tomislav Šmuc. (2013). Semi-Supervised Learning for Quantitative Structure-Activity Modeling. Institutional Repository of the Ruđer Bošković Institute (Ruđer Bošković Institute). 37(2). 173–179. 12 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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2026