Mabel Sánchez

703 total citations
47 papers, 491 citations indexed

About

Mabel Sánchez is a scholar working on Control and Systems Engineering, Statistics, Probability and Uncertainty and Analytical Chemistry. According to data from OpenAlex, Mabel Sánchez has authored 47 papers receiving a total of 491 indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Control and Systems Engineering, 15 papers in Statistics, Probability and Uncertainty and 8 papers in Analytical Chemistry. Recurrent topics in Mabel Sánchez's work include Fault Detection and Control Systems (34 papers), Advanced Control Systems Optimization (17 papers) and Advanced Statistical Process Monitoring (12 papers). Mabel Sánchez is often cited by papers focused on Fault Detection and Control Systems (34 papers), Advanced Control Systems Optimization (17 papers) and Advanced Statistical Process Monitoring (12 papers). Mabel Sánchez collaborates with scholars based in Argentina, United States and Australia. Mabel Sánchez's co-authors include Miguel J. Bagajewicz, José A. Romagnoli, Ricardo A. Maronna, Qiyou Jiang, Ignacio Ponzoni, Nélida B. Brignole, Adriana Brandolin, José L. Hernández, José L. Hernández-Ramos and J. M. Maestre and has published in prestigious journals such as SHILAP Revista de lepidopterología, Industrial & Engineering Chemistry Research and AIChE Journal.

In The Last Decade

Mabel Sánchez

46 papers receiving 457 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mabel Sánchez Argentina 14 405 115 85 73 59 47 491
Derya B. Özyurt United States 6 166 0.4× 39 0.3× 43 0.5× 40 0.5× 22 0.4× 6 328
Shima Khatibisepehr Canada 10 500 1.2× 91 0.8× 92 1.1× 150 2.1× 11 0.2× 17 561
Willy Wojsznis United States 13 333 0.8× 51 0.4× 42 0.5× 89 1.2× 48 0.8× 27 439
Ping Duan China 6 298 0.7× 98 0.9× 97 1.1× 84 1.2× 23 0.4× 8 401
G.M. Stanley United States 8 314 0.8× 70 0.6× 64 0.8× 57 0.8× 9 0.2× 13 368
S.L. Shah Canada 13 802 2.0× 74 0.6× 36 0.4× 107 1.5× 20 0.3× 27 880
Swanand Khare India 11 320 0.8× 47 0.4× 86 1.0× 128 1.8× 5 0.1× 33 475
Michał Syfert Poland 10 341 0.8× 49 0.4× 15 0.2× 104 1.4× 25 0.4× 41 416
Bao Lin Denmark 7 312 0.8× 22 0.2× 86 1.0× 163 2.2× 12 0.2× 9 473
Mark Kotanchek United States 5 380 0.9× 67 0.6× 162 1.9× 264 3.6× 9 0.2× 10 501

Countries citing papers authored by Mabel Sánchez

Since Specialization
Citations

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

Fields of papers citing papers by Mabel Sánchez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mabel Sánchez

This figure shows the co-authorship network connecting the top 25 collaborators of Mabel Sánchez. A scholar is included among the top collaborators of Mabel Sánchez 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 Mabel Sánchez. Mabel Sánchez 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
1.
Sánchez, Mabel, et al.. (2023). An efficient methodology to select high-performance M-estimators for robust data reconciliation. Computers & Chemical Engineering. 176. 108297–108297. 2 indexed citations
2.
Asteasuain, Mariano, et al.. (2020). Efficient and robust state estimation: Application to a copolymerization process. The Canadian Journal of Chemical Engineering. 99(S1). 2 indexed citations
3.
Hernández, José Alberto, et al.. (2019). Hybrid Simulated Annealing for Optimal Cost Instrumentation in Chemical Plants. SHILAP Revista de lepidopterología. 2 indexed citations
4.
Sánchez, Mabel, et al.. (2019). Dynamic System State Estimation and Outlier Detection Using Robust Data Reconciliation. SHILAP Revista de lepidopterología. 1 indexed citations
5.
Hernández, José L., et al.. (2019). Optimal Instrumentation: Adjustment and Hybridization of a Simulated AnnealingBased Technique. El Servicio de Difusión de la Creación Intelectual (National University of La Plata).
6.
Sánchez, Mabel, et al.. (2016). Sensor Location for Enhancing Fault Diagnosis. Industrial & Engineering Chemistry Research. 55(32). 8830–8836. 2 indexed citations
7.
Sánchez, Mabel, et al.. (2016). Bioprocess statistical control: Identification stage based on hierarchical clustering. Process Biochemistry. 51(12). 1919–1929. 2 indexed citations
8.
Sánchez, Mabel, et al.. (2016). Optimal Sensor Network Upgrade for Fault Detection Using Principal Component Analysis. Industrial & Engineering Chemistry Research. 55(8). 2359–2370. 6 indexed citations
9.
Hernández, José L., et al.. (2013). A new metaheuristic based approach for the design of sensor networks. Computers & Chemical Engineering. 55. 83–96. 4 indexed citations
10.
Benetti, Paula, J. Robert Kelly, Mabel Sánchez, & Álvaro Della Bona. (2011). Influence of thermal gradients on stress state of veneered restorations. Dental Materials. 27. e77–e77. 2 indexed citations
11.
Hernández, José L., et al.. (2009). Design of Sensor Networks for Chemical Plants Based on Meta-Heuristics. Algorithms. 2(1). 259–281. 5 indexed citations
12.
Ponzoni, Ignacio, et al.. (2002). A Symbolic Derivation Approach for Redundancy Analysis. Industrial & Engineering Chemistry Research. 41(23). 5692–5701. 4 indexed citations
13.
Ponzoni, Ignacio, Gustavo E. Vázquez, Mabel Sánchez, & Nélida B. Brignole. (2001). Parallel observability analysis on networks of workstations. Computers & Chemical Engineering. 25(7-8). 997–1002. 2 indexed citations
14.
Hernández-Ramos, José L., et al.. (2001). An Evolutionary Approach for the Design of Nonredundant Sensor Networks. Industrial & Engineering Chemistry Research. 40(23). 5578–5584. 22 indexed citations
15.
Sánchez, Mabel & Miguel J. Bagajewicz. (2000). On the Impact of Corrective Maintenance in the Design of Sensor Networks. Industrial & Engineering Chemistry Research. 39(4). 977–981. 17 indexed citations
16.
Bagajewicz, Miguel J. & Mabel Sánchez. (2000). Reallocation and upgrade of instrumentation in process plants. Computers & Chemical Engineering. 24(8). 1945–1959. 25 indexed citations
17.
Bagajewicz, Miguel J. & Mabel Sánchez. (2000). Cost-optimal design of reliable sensor networks. Computers & Chemical Engineering. 23(11-12). 1757–1762. 41 indexed citations
18.
Bagajewicz, Miguel J., Qiyou Jiang, & Mabel Sánchez. (1999). Performance evaluation of PCA tests for multiple gross error identification. Computers & Chemical Engineering. 23. S589–S592. 2 indexed citations
19.
Bagajewicz, Miguel J. & Mabel Sánchez. (1999). Sensor network design and upgrade for plant parameter estimation. Computers & Chemical Engineering. 23. S593–S596. 5 indexed citations
20.
Sánchez, Mabel & José A. Romagnoli. (1996). Use of orthogonal transformations in data classification-reconciliation. Computers & Chemical Engineering. 20(5). 483–493. 44 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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