Luca Stefanutti

2.1k citations
66 papers · 807 indexed · h-index 18
Topics
Intelligent Tutoring Systems and Adaptive Learning (43 papers)AI-based Problem Solving and Planning (17 papers)Bayesian Modeling and Causal Inference (16 papers)
Partner nations
ItalyGermanyAustria

In The Last Decade

Luca Stefanutti

59 papers receiving 785 citations

Peers

Luca Stefanutti
Comparison fields: 5 of 64
  • Artificial Intelligence 591
  • Management Science and Operations Research 149
  • Information Systems 120
  • Computer Science Applications 119
  • Developmental and Educational Psychology 104
Replace Jürgen Heller with:
Jürgen Heller Germany
C. Brew United States
André A. Rupp United States
Evangelos Triantafillou Greece
Duanli Yan United States
Derrick Higgins United States
Chia-Yi Chiu United States
Hongzhi Yang Australia
Adam Darlow United States
Masaki Uto Japan
Luca Stefanutti relative to Jürgen Heller Germany Jürgen Heller's profile →
Citations per field
00.5×
Jürgen Heller · 1×
Citations per year

Countries citing papers authored by Luca Stefanutti

Since Specialization
Citations

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

Fields of papers citing papers by Luca Stefanutti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luca Stefanutti

This figure shows the co-authorship network connecting the top 25 collaborators of Luca Stefanutti. A scholar is included among the top collaborators of Luca Stefanutti 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 Luca Stefanutti. Luca Stefanutti 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
#WorkIndexed citations
1 1
2 0
3 4
4 1
5 0
6 3
7 2
8 11
9 11
10 21
11 17
12 19
13 21
14 23
15 58
16 2
17 9
18
IDENTIFIABILITY AND GOODNESS OF RECOVERY IN THE CONSTRAINED GAIN-LOSS MODEL
0
19 10
20
Skill assessment in problem solving and task simulation
1

About Luca Stefanutti

Luca Stefanutti is a scholar working on Computer Science Applications, Artificial Intelligence and Management Science and Operations Research, having authored 66 papers that have together received 807 indexed citations. Recurring topics across this work include Intelligent Tutoring Systems and Adaptive Learning (43 papers), AI-based Problem Solving and Planning (17 papers) and Bayesian Modeling and Causal Inference (16 papers). The work is most often cited by research in Computer Science Applications (119 citations), Artificial Intelligence (591 citations) and Management Science and Operations Research (149 citations). Luca Stefanutti has collaborated with scholars based in Italy, Germany and Austria. Frequent co-authors include Egidio Robusto, Pasquale Anselmi, Debora de Chiusole, Andrea Spoto, Giulio Vidotto, Jürgen Heller, Dietrich Albert, D. Bisello, E. Noah and A. Candelori. Their work appears in journals such as Psychological Methods, Psychometrika and Behavior Research Methods.

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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