Stefano Teso

868 citations
37 papers · 327 · h-index 10

Impact in

    • Explainable Artificial Intelligence (XAI)
    • AI-based Problem Solving and Planning
    • Machine Learning and Algorithms
    • Topic Modeling
    • Machine Learning and Data Classification
    • Semantic Web and Ontologies

Papers in

Stefano Teso

35 papers receiving 324 citations

Peers

Stefano Teso
Comparison fields: 5 of 70
  • Health Informatics 19
  • Artificial Intelligence 216
  • Computer Networks and Communications 60
  • Information Systems and Management 18
  • Safety Research 20
Replace Ashwin Paranjape with:
Ashwin Paranjape United States
Henry Corrigan-Gibbs United States
Karsten Tolle Germany
Christopher A. Choquette-Choo United States
Leo Gao Japan
Daye Nam United States
Albert Webson United States
Sahar Abdelnabi Germany
Wanjun Zhong China
Dónal Doyle Ireland
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Citations per field
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Citations per year

Countries citing papers authored by Stefano Teso

Since Specialization
Citations

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

Fields of papers citing papers by Stefano Teso

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Stefano Teso, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Stefano Teso Line = papers co-authored together Stefano Teso links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201990
2 201526
3 202322
4 201821
5 201820
6 202220
7 202116
8 201411
9 201711
10 201710
11 20188
12 20147
13 20207
14 20226
15 20136
16
Right for the Wrong Scientific Reasons: Revising Deep Networks by Interacting with their Explanations.
20205
17 20184
18
A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference
20214
19 20193
20 20203

About Stefano Teso

Stefano Teso is a scholar working on Artificial Intelligence, Computer Networks and Communications, Signal Processing, Computational Theory and Mathematics and Management Science and Operations Research, having authored 37 papers that have together received 327 indexed citations. Recurring topics across this work include Constraint Satisfaction and Optimization (9 papers), Machine Learning and Algorithms (7 papers), AI-based Problem Solving and Planning (7 papers), Machine Learning and Data Classification (5 papers), Explainable Artificial Intelligence (XAI) (5 papers), Data Management and Algorithms (4 papers), Multi-Criteria Decision Making (3 papers) and Context-Aware Activity Recognition Systems (3 papers). The work is most often cited by research in Health Informatics (19 citations), Artificial Intelligence (216 citations), Computer Networks and Communications (60 citations), Information Systems and Management (18 citations) and Safety Research (20 citations). Stefano Teso has collaborated with scholars based in Italy, Belgium and China. Frequent co-authors include Kristian Kersting, Andrea Passerini, Luc De Raedt, Roberto Sebastiani, Elizabeth Daly, Öznur Alkan, Bruno Lepri, Oliver Hinz, Qiang Shen and Jacopo Staiano. Their work appears in journals such as BMC Bioinformatics, Artificial Intelligence, EPJ Data Science, Electronics and Data Mining and Knowledge Discovery.

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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