Stefano Coniglio

811 total citations
48 papers, 450 citations indexed

About

Stefano Coniglio is a scholar working on Electrical and Electronic Engineering, Management Science and Operations Research and Computer Networks and Communications. According to data from OpenAlex, Stefano Coniglio has authored 48 papers receiving a total of 450 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Electrical and Electronic Engineering, 10 papers in Management Science and Operations Research and 9 papers in Computer Networks and Communications. Recurrent topics in Stefano Coniglio's work include Game Theory and Applications (7 papers), Facility Location and Emergency Management (6 papers) and Advanced Optical Network Technologies (6 papers). Stefano Coniglio is often cited by papers focused on Game Theory and Applications (7 papers), Facility Location and Emergency Management (6 papers) and Advanced Optical Network Technologies (6 papers). Stefano Coniglio collaborates with scholars based in Italy, United Kingdom and Germany. Stefano Coniglio's co-authors include E. Amaldi, Arie M. C. A. Koster, Fabio Furini, Pablo San Segundo, Nicola Gatti, Luca G. Gianoli, Antonio Capone, Ivana Ljubić, Nicola Basilico and Antonio Martínez-Sykora and has published in prestigious journals such as SHILAP Revista de lepidopterología, European Journal of Operational Research and Energy.

In The Last Decade

Stefano Coniglio

45 papers receiving 440 citations

Peers

Stefano Coniglio

CNC

EEE

IME

MSOR

CTM

Dritan Nace France

Jason J. Sauppe United States

Eli V. Olinick United States

Walid Ben‐Ameur France

Katerina Papadaki United Kingdom

Dong‐Yuh Yang Taiwan

José Luís Santos Portugal

Yves Caseau France

A. V. Pechinkin Russia

Dritan Nace France

Stefano Coniglio

296 ×1.5

CNC

217 ×1.5

EEE

131 ×1.5

IME

91 ×1.4

MSOR

42 ×1.0

CTM

Citations per year, relative to Stefano Coniglio Stefano Coniglio (= 1×) peers Dritan Nace

Countries citing papers authored by Stefano Coniglio

Since Specialization

Citations

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

Fields of papers citing papers by Stefano Coniglio

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stefano Coniglio

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

All Works

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20 of 20 papers shown

Coniglio, Stefano, et al.. (2025). Bridging theory and practice: Efficiently solving the unit commitment problem in production cost models. Energy. 322. 135454–135454.

Fiorini, Stefano, Stefano Coniglio, Michele Ciavotta, & Enza Messina. (2024). Graph Learning in 4D: A Quaternion-Valued Laplacian to Enhance Spectral GCNs. Proceedings of the AAAI Conference on Artificial Intelligence. 38(11). 12006–12015. 1 indexed citations

Coniglio, Stefano, et al.. (2023). Correlation analysis of deep learning methods in S‐ICD screening. Annals of Noninvasive Electrocardiology. 28(4). e13056–e13056. 2 indexed citations

Fiorini, Stefano, Stefano Coniglio, Michele Ciavotta, & Enza Messina. (2023). SigMaNet: One Laplacian to Rule Them All. Proceedings of the AAAI Conference on Artificial Intelligence. 37(6). 7568–7576. 7 indexed citations

Coniglio, Stefano, et al.. (2023). Deep learning and hyperparameter optimization for assessing one’s eligibility for a subcutaneous implantable cardioverter-defibrillator. Annals of Operations Research. 328(1). 309–335. 1 indexed citations

Coniglio, Stefano, et al.. (2022). Deep learning-based insights on T:R ratio behaviour during prolonged screening for S-ICD eligibility. Journal of Interventional Cardiac Electrophysiology. 68(7). 1387–1397. 3 indexed citations

Coniglio, Stefano, et al.. (2022). Role of deep learning methods in screening for subcutaneous implantable cardioverter defibrillator in heart failure. Annals of Noninvasive Electrocardiology. 28(1). e13028–e13028. 3 indexed citations

Coniglio, Stefano & Stefano Gualandi. (2021). Optimizing over the Closure of Rank Inequalities with a Small Right-Hand Side for the Maximum Stable Set Problem via Bilevel Programming. INFORMS journal on computing. 34(2). 1006–1023. 1 indexed citations

Coniglio, Stefano, et al.. (2019). Computing Optimal Ex Ante Correlated Equilibria in Two-Player Sequential Games. ePrints Soton (University of Southampton). 909–917. 2 indexed citations

10.

Segundo, Pablo San, Stefano Coniglio, Fabio Furini, & Ivana Ljubić. (2019). A new branch-and-bound algorithm for the maximum edge-weighted clique problem. European Journal of Operational Research. 278(1). 76–90. 18 indexed citations

11.

Coniglio, Stefano, et al.. (2017). Lot sizing with storage losses under demand uncertainty. Journal of Combinatorial Optimization. 36(3). 763–788. 7 indexed citations

12.

Basilico, Nicola, Stefano Coniglio, & Nicola Gatti. (2016). Methods for Finding Leader-Follower Equilibria with Multiple Followers: (Extended Abstract). ePrints Soton (University of Southampton). 1363–1364.

13.

Basilico, Nicola, Stefano Coniglio, & Nicola Gatti. (2016). Methods for Finding Leader-Follower Equilibria with Multiple Followers: (Extended Abstract). Adaptive Agents and Multi-Agents Systems. 1363–1364. 4 indexed citations

14.

Amaldi, E., et al.. (2016). On the computational complexity of the virtual network embedding problem. Electronic Notes in Discrete Mathematics. 52. 213–220. 103 indexed citations

15.

Amaldi, E., Stefano Coniglio, & Leonardo Taccari. (2016). Discrete optimization methods to fit piecewise affine models to data points. Computers & Operations Research. 75. 214–230. 9 indexed citations

16.

Coniglio, Stefano. (2013). Bound-optimal cutting planes. RWTH Publications (RWTH Aachen). 59–62.

17.

Amaldi, E., Stefano Coniglio, & Leonardo Taccari. (2012). k-Piecewise Affine Model Fitting: Heuristics Based on Multiway Linear Classification.. ePrints Soton (University of Southampton). 16–19. 2 indexed citations

18.

Coniglio, Stefano. (2011). The impact of the norm on the k-Hyperplane Clustering problem: relaxations, restrictions, approximation factors, and exact formulations.. Aisberg (University of Bergamo). 118–121. 1 indexed citations

19.

Amaldi, E., Stefano Coniglio, & Leonardo Taccari. (2011). Formulations and heuristics for the k-Piecewise Affine Model Fitting problem. ePrints Soton (University of Southampton). 48–51. 2 indexed citations

20.

Amaldi, E., et al.. (2009). k-Hyperplane Clustering Problem: Column Generation and a Metaheuristic.. ePrints Soton (University of Southampton). 355–358. 3 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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