Mario Sznaier

6.2k citations
277 papers · 3.5k indexed · h-index 28

Mario Sznaier

254 papers receiving 3.4k citations

Peers

Mario Sznaier
Comparison fields: 5 of 127
  • Control and Systems Engineering 2.2k
  • Computer Vision and Pattern Recognition 869
  • Statistics, Probability and Uncertainty 178
  • Numerical Analysis 134
  • Computational Mathematics 13
Replace Andrea Garulli with:
Andrea Garulli Italy
Alessandro Chiuso Italy
G.W. Irwin United Kingdom
Wook Hyun Кwon South Korea
Youshen Xia China
Senchun Chai China
Roy S. Smith Switzerland
Michel Fliess France
M.J. Grimble United Kingdom
Dongsheng Guo China
Mario Sznaier relative to Andrea Garulli Italy Andrea Garulli's profile →
Citations per field
00.5×1.5×2.0×
Andrea Garulli · 1×
Citations per year

Countries citing papers authored by Mario Sznaier

Since Specialization
Citations

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

Fields of papers citing papers by Mario Sznaier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Mario Sznaier, 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 Mario Sznaier Line = papers co-authored together Mario Sznaier links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20240
4 20241
5 20241
6 20233
7 20220
8 202032
9
Solving Interpretable Kernel Dimensionality Reduction
20195
10 20191
11 20185
12 201830
13 201716
14 20174
15 201224
16 20093
17 20064
18 200516
19 200448
20 199919

About Mario Sznaier

Mario Sznaier is a scholar working on Control and Systems Engineering, Statistics, Probability and Uncertainty and Numerical Analysis, having authored 277 papers that have together received 3.5k indexed citations. Recurring topics across this work include Control Systems and Identification (157 papers), Advanced Control Systems Optimization (106 papers), Fault Detection and Control Systems (84 papers), Stability and Control of Uncertain Systems (75 papers), Probabilistic and Robust Engineering Design (27 papers), Advanced Vision and Imaging (26 papers), Sparse and Compressive Sensing Techniques (24 papers) and Model Reduction and Neural Networks (21 papers). The work is most often cited by research in Control and Systems Engineering (2.2k citations), Computer Vision and Pattern Recognition (869 citations) and Statistics, Probability and Uncertainty (178 citations). Mario Sznaier has collaborated with scholars based in United States, Italy and Israel. Frequent co-authors include Octavia Camps, Ricardo Sánchez‐Peña, Constantino Lagoa, M.J. Damborg, Franco Blanchini, Necmiye Özay, Caglayan Dicle, Mustafa Ayazoğlu, Tamer Inanc and Tao Ding. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Automatic Control and Automatica.

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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