Sandro Saitta

472 citations
18 papers · 259 indexed · h-index 8

Impact in

Papers in

Sandro Saitta

17 papers receiving 234 citations

Peers

Sandro Saitta
Comparison fields: 5 of 60
  • Civil and Structural Engineering 128
  • Statistics, Probability and Uncertainty 31
  • Artificial Intelligence 75
  • Statistical and Nonlinear Physics 17
  • Control and Systems Engineering 30
Replace Jice Zeng with:
Jice Zeng United States
Jihun Yi South Korea
Marcelo Espinoza Belgium
Yeboon Yun Japan
Rui Zhu China
Marcelo G. Rubinstein Brazil
Shengyu Wu China
M. Li United States
Martin Mevissen Ireland
Sandro Saitta relative to Jice Zeng United States Jice Zeng's profile →
Citations per field
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Citations per year

Countries citing papers authored by Sandro Saitta

Since Specialization
Citations

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

Fields of papers citing papers by Sandro Saitta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 8 scholars most cited alongside Sandro Saitta, 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 Sandro Saitta Line = papers co-authored together Sandro Saitta links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1
Data Mining: Applications in Civil Engineering
20097
2 200915
3 200833
4 200831
5 200847
6 20082
7
System Identification: Data Mining to Explore Multiple Models
20071
8 200716
9 20076
10 20071
11 20076
12
Data mining for decision support in multiple-model system identification
20061
13 20068
14
Challenges of data interpretation
20065
15 20063
16 20053
17 200546
18 199328

About Sandro Saitta

Sandro Saitta is a scholar working on Civil and Structural Engineering, Control and Systems Engineering, Artificial Intelligence, Statistics, Probability and Uncertainty and Statistical and Nonlinear Physics, having authored 18 papers that have together received 259 indexed citations. Recurring topics across this work include Structural Health Monitoring Techniques (9 papers), Fault Detection and Control Systems (7 papers), Neural Networks and Applications (5 papers), Probabilistic and Robust Engineering Design (2 papers), Infrastructure Maintenance and Monitoring (2 papers), AI-based Problem Solving and Planning (2 papers), Control Systems and Identification (1 paper) and Scientific Research and Discoveries (1 paper). The work is most often cited by research in Civil and Structural Engineering (128 citations), Statistics, Probability and Uncertainty (31 citations), Artificial Intelligence (75 citations), Statistical and Nonlinear Physics (17 citations) and Control and Systems Engineering (30 citations). Sandro Saitta has collaborated with scholars based in Switzerland, Singapore and United States. Frequent co-authors include Ian F. C. Smith, Benny Raphael, Prakash Kripakaran, Suraj Ravindran, Giuseppe Molinari, S Caponnetto, Roberto Parodi and Francesco Sardanelli. Their work appears in journals such as Advanced Engineering Informatics, Journal of Computing in Civil Engineering, Journal of Structural Engineering, Journal of Computer Assisted Tomography and Intelligent Data Analysis.

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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