Algo Carè

804 total citations
42 papers, 578 citations indexed

About

Algo Carè is a scholar working on Statistics, Probability and Uncertainty, Control and Systems Engineering and Management Science and Operations Research. According to data from OpenAlex, Algo Carè has authored 42 papers receiving a total of 578 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Statistics, Probability and Uncertainty, 17 papers in Control and Systems Engineering and 12 papers in Management Science and Operations Research. Recurrent topics in Algo Carè's work include Control Systems and Identification (17 papers), Probabilistic and Robust Engineering Design (16 papers) and Fault Detection and Control Systems (9 papers). Algo Carè is often cited by papers focused on Control Systems and Identification (17 papers), Probabilistic and Robust Engineering Design (16 papers) and Fault Detection and Control Systems (9 papers). Algo Carè collaborates with scholars based in Italy, Australia and Hungary. Algo Carè's co-authors include Marco C. Campi, Simone Garatti, Erik Weyer, Sergio M. Savaresi, Enrico Camporeale, Joseph E. Borovsky, Simone Formentin, Balázs Csanád Csáji, Hasan Arshad Nasir and Federico Ramponi and has published in prestigious journals such as IEEE Transactions on Automatic Control, Automatica and IEEE Transactions on Power Systems.

In The Last Decade

Algo Carè

39 papers receiving 552 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Algo Carè Italy	13	282	125	108	96	80	42	578
M. Raghavachari United States	16	74 0.3×	65 0.5×	144 1.3×	53 0.6×	32 0.4×	37	799
Ioannis Giagkiozis United Kingdom	10	75 0.3×	78 0.6×	39 0.4×	272 2.8×	28 0.3×	15	707
Paresh Date United Kingdom	17	313 1.1×	121 1.0×	41 0.4×	217 2.3×	41 0.5×	67	794
Hamid Laga Australia	3	67 0.2×	18 0.1×	43 0.4×	172 1.8×	17 0.2×	3	470
Shan Ba United States	9	41 0.1×	200 1.6×	168 1.6×	108 1.1×	6 0.1×	15	524
Ismael Sánchez Spain	12	102 0.4×	100 0.8×	71 0.7×	96 1.0×	7 0.1×	30	616
Jun Zhan China	10	128 0.5×	176 1.4×	49 0.5×	176 1.8×	11 0.1×	21	489
Rui Yao United States	17	398 1.4×	27 0.2×	38 0.4×	64 0.7×	6 0.1×	66	869
Brian Weaver United States	11	51 0.2×	62 0.5×	106 1.0×	17 0.2×	5 0.1×	41	449

Countries citing papers authored by Algo Carè

Since Specialization

Citations

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

Fields of papers citing papers by Algo Carè

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Algo Carè

This figure shows the co-authorship network connecting the top 25 collaborators of Algo Carè. A scholar is included among the top collaborators of Algo Carè 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 Algo Carè. Algo Carè is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Garatti, Simone, Algo Carè, & Marco C. Campi. (2022). Complexity Is an Effective Observable to Tune Early Stopping in Scenario Optimization. IEEE Transactions on Automatic Control. 68(2). 928–942. 9 indexed citations

Camporeale, Enrico & Algo Carè. (2021). ACCRUE: ACCURATE AND RELIABLE UNCERTAINTY ESTIMATE IN DETERMINISTIC MODELS. International Journal for Uncertainty Quantification. 11(4). 81–94. 9 indexed citations

Campi, Marco C., et al.. (2021). A Theory of the Risk for Empirical CVaR with Application to Portfolio Selection. Journal of Systems Science and Complexity. 34(5). 1879–1894. 6 indexed citations

Carè, Algo, et al.. (2020). Novel Bounds on the Probability of Misclassification in Majority Voting: Leveraging the Majority Size. IEEE Control Systems Letters. 5(5). 1513–1518. 1 indexed citations

Carè, Algo, et al.. (2020). A study on majority-voting classifiers with guarantees on the probability of error. IFAC-PapersOnLine. 53(2). 1013–1018. 3 indexed citations

Carè, Algo, et al.. (2019). Consensus and Reliability: The Case of Two Binary Classifiers. IFAC-PapersOnLine. 52(20). 73–78. 2 indexed citations

Garatti, Simone, Marco C. Campi, & Algo Carè. (2019). On a class of interval predictor models with universal reliability. Automatica. 110. 108542–108542. 22 indexed citations

Carè, Algo, et al.. (2019). Parameter-Dependent Poisson Equations: Tools for Stochastic Approximation in a Markovian Framework. Institutional Research Information System (Università degli Studi di Brescia). 2259–2264.

Formentin, Simone, Marco C. Campi, Algo Carè, & Sergio M. Savaresi. (2019). Deterministic continuous-time Virtual Reference Feedback Tuning (VRFT) with application to PID design. Systems & Control Letters. 127. 25–34. 73 indexed citations

10.

Xie, Le, Marco C. Campi, Simone Garatti, et al.. (2018). Scenario-Based Economic Dispatch With Tunable Risk Levels in High-Renewable Power Systems. IEEE Transactions on Power Systems. 34(6). 5103–5114. 48 indexed citations

11.

Nasir, Hasan Arshad, Algo Carè, & Erik Weyer. (2018). A Scenario-Based Stochastic MPC Approach for Problems With Normal and Rare Operations With an Application to Rivers. IEEE Transactions on Control Systems Technology. 27(4). 1397–1410. 17 indexed citations

12.

Baronio, Fabio, et al.. (2017). Ventricular defibrillation: Classification with G.E.M. and a roadmap for future investigations. Institutional Research Information System (Università degli Studi di Brescia). 2718–2723. 6 indexed citations

13.

Carè, Algo, Balázs Csanád Csáji, Marco C. Campi, & Erik Weyer. (2017). Finite-Sample System Identification: An Overview and a New Correlation Method. IEEE Control Systems Letters. 2(1). 61–66. 41 indexed citations

14.

Nasir, Hasan Arshad, Algo Carè, & Erik Weyer. (2016). A randomised approach to Multiple Chance-Constrained Problems: An application to flood avoidance. Institutional Research Information System (Università degli Studi di Brescia). 6216–6221. 1 indexed citations

15.

Carè, Algo, Simone Garatti, & Marco C. Campi. (2016). A Coverage Theory for Least Squares. Journal of the Royal Statistical Society Series B (Statistical Methodology). 79(5). 1367–1389. 12 indexed citations

16.

Carè, Algo, Simone Garatti, & Marco C. Campi. (2015). Scenario Min-Max Optimization and the Risk of Empirical Costs. SIAM Journal on Optimization. 25(4). 2061–2080. 41 indexed citations

17.

Nasir, Hasan Arshad, Algo Carè, & Erik Weyer. (2015). A randomised approach to flood control using Value-at-Risk. Institutional Research Information System (Università degli Studi di Brescia). 3939–3944. 7 indexed citations

18.

Carè, Algo, Simone Garatti, & Marco C. Campi. (2014). FAST—Fast Algorithm for the Scenario Technique. Operations Research. 62(3). 662–671. 36 indexed citations

19.

Carè, Algo, Simone Garatti, & Marco C. Campi. (2013). Least squares estimates and the coverage of least squares costs. Institutional Research Information System (Università degli Studi di Brescia). 6025–6030. 1 indexed citations

20.

Carè, Algo, Simone Garatti, & Marco C. Campi. (2011). Randomized min-max optimization: The exact risk of multiple cost levels. 30. 7794–7799. 2 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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