Diego Manzanas Lopez

518 total citations
18 papers, 125 citations indexed

About

Diego Manzanas Lopez is a scholar working on Artificial Intelligence, Control and Systems Engineering and Automotive Engineering. According to data from OpenAlex, Diego Manzanas Lopez has authored 18 papers receiving a total of 125 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 11 papers in Control and Systems Engineering and 5 papers in Automotive Engineering. Recurrent topics in Diego Manzanas Lopez's work include Adversarial Robustness in Machine Learning (14 papers), Fault Detection and Control Systems (10 papers) and Smart Grid Security and Resilience (5 papers). Diego Manzanas Lopez is often cited by papers focused on Adversarial Robustness in Machine Learning (14 papers), Fault Detection and Control Systems (10 papers) and Smart Grid Security and Resilience (5 papers). Diego Manzanas Lopez collaborates with scholars based in United States, Germany and United Kingdom. Diego Manzanas Lopez's co-authors include Taylor T. Johnson, Hoang-Dung Tran, Patrick Musau, Luan Viet Nguyen, Xiaodong Yang, Weiming Xiang, Nathaniel Hamilton, Stanley Bak, Christian Schilling and Xenofon Koutsoukos and has published in prestigious journals such as ACM Transactions on Embedded Computing Systems, Formal Aspects of Computing and AIAA Scitech 2021 Forum.

In The Last Decade

Diego Manzanas Lopez

17 papers receiving 123 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Diego Manzanas Lopez United States 8 92 45 24 20 19 18 125
Patrick Musau United States 7 59 0.6× 28 0.6× 14 0.6× 12 0.6× 17 0.9× 13 81
Bettina Könighofer Austria 7 72 0.8× 25 0.6× 42 1.8× 4 0.2× 10 0.5× 15 134
Daniel J. Fremont United States 6 68 0.7× 11 0.2× 31 1.3× 7 0.3× 26 1.4× 10 118
Jean‐Michel Ilié France 7 42 0.5× 12 0.3× 7 0.3× 7 0.3× 7 0.4× 25 87
Youssef Laarouchi France 6 29 0.3× 28 0.6× 15 0.6× 62 3.1× 20 1.1× 10 115
Panagiotis Kouvaros United Kingdom 9 154 1.7× 13 0.3× 22 0.9× 10 0.5× 2 0.1× 18 190
Nils Quetschlich Germany 7 130 1.4× 32 0.7× 2 0.1× 33 1.6× 56 2.9× 14 198
Alfons Geser Germany 8 124 1.3× 10 0.2× 7 0.3× 6 0.3× 26 1.4× 25 203
Hardi Hungar Germany 7 70 0.8× 12 0.3× 68 2.8× 7 0.3× 15 0.8× 12 138
Adnane Saoud France 9 28 0.3× 100 2.2× 13 0.5× 6 0.3× 2 0.1× 39 186

Countries citing papers authored by Diego Manzanas Lopez

Since Specialization
Citations

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

Fields of papers citing papers by Diego Manzanas Lopez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Diego Manzanas Lopez. 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 Diego Manzanas Lopez. The network helps show where Diego Manzanas Lopez may publish in the future.

Co-authorship network of co-authors of Diego Manzanas Lopez

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

All Works

18 of 18 papers shown
1.
Lopez, Diego Manzanas, et al.. (2024). Case Study: Neural Network Malware Detection Verification for Feature and Image Datasets. 127–137. 1 indexed citations
2.
Bogomolov, Sergiy, et al.. (2023). Online Reachability Analysis and Space Convexification for Autonomous Racing. Electronic Proceedings in Theoretical Computer Science. 395. 95–112. 1 indexed citations
3.
Lopez, Diego Manzanas, et al.. (2023). ARCH-COMP23 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants. EPiC series in computing. 96. 89–51. 9 indexed citations
4.
Lopez, Diego Manzanas, Matthias Althoff, Luis Benet, et al.. (2022). ARCH-COMP22 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants. EPiC series in computing. 90. 142–98. 9 indexed citations
5.
Hamilton, Nathaniel, Patrick Musau, Diego Manzanas Lopez, & Taylor T. Johnson. (2022). Zero-Shot Policy Transfer in Autonomous Racing: Reinforcement Learning vs Imitation Learning. 11–20. 9 indexed citations
6.
Lopez, Diego Manzanas, Taylor T. Johnson, Stanley Bak, Hoang-Dung Tran, & Kerianne L. Hobbs. (2022). Evaluation of Neural Network Verification Methods for Air-to-Air Collision Avoidance. 31(1). 1–17. 7 indexed citations
7.
Musau, Patrick, et al.. (2022). On Using Real-Time Reachability for the Safety Assurance of Machine Learning Controllers. 1–10. 6 indexed citations
8.
Lopez, Diego Manzanas, Taylor T. Johnson, Hoang-Dung Tran, et al.. (2021). Verification of Neural Network Compression of ACAS Xu Lookup Tables with Star Set Reachability. AIAA Scitech 2021 Forum. 6 indexed citations
9.
Johnson, Taylor T., Diego Manzanas Lopez, Luis Benet, et al.. (2021). ARCH-COMP21 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants. EPiC series in computing. 7 indexed citations
10.
Tran, Hoang-Dung, Diego Manzanas Lopez, Patrick Musau, et al.. (2021). Verification of piecewise deep neural networks: a star set approach with zonotope pre-filter. Formal Aspects of Computing. 33(4-5). 519–545. 7 indexed citations
11.
Johnson, Taylor T., Diego Manzanas Lopez, Patrick Musau, et al.. (2020). ARCH-COMP20 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants. EPiC series in computing. 74. 107–73. 6 indexed citations
12.
Tran, Hoang-Dung, Diego Manzanas Lopez, Xiaodong Yang, et al.. (2020). Demo: The Neural Network Verification (NNV) Tool. 2 indexed citations
13.
Lopez, Diego Manzanas, et al.. (2020). Case Study: Safety Verification of an Unmanned Underwater Vehicle. 189–195. 3 indexed citations
14.
Lopez, Diego Manzanas, Patrick Musau, Hoang-Dung Tran, & Taylor T. Johnson. (2019). Verification of Closed-loop Systems with Neural Network Controllers. EPiC series in computing. 61. 201–190. 8 indexed citations
15.
Lopez, Diego Manzanas, Patrick Musau, Hoang-Dung Tran, et al.. (2019). ARCH-COMP19 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants. EPiC series in computing. 61. 103–85. 7 indexed citations
16.
Tran, Hoang-Dung, Patrick Musau, Diego Manzanas Lopez, et al.. (2019). Parallelizable Reachability Analysis Algorithms for Feed-Forward Neural Networks. 51–60. 26 indexed citations
17.
Tran, Hoang-Dung, et al.. (2019). Safety Verification of Cyber-Physical Systems with Reinforcement Learning Control. ACM Transactions on Embedded Computing Systems. 18(5s). 1–22. 11 indexed citations
18.
Musau, Patrick, Diego Manzanas Lopez, Hoang-Dung Tran, & Taylor T. Johnson. (2018). Linear Differential-Algebraic Equations (Benchmark Proposal). EPiC series in computing. 54. 174–162.

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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2026