Diego Manzanas Lopez
- Artificial Intelligence top 10%
- Control and Systems Engineering
- Software top 10%
- Electrical and Electronic Engineering
- Automotive Engineering
- Co-authors
- Taylor T. JohnsonHoang-Dung TranPatrick MusauXiaodong YangLuan Viet NguyenWeiming XiangNathaniel HamiltonChristian Schilling
- Topics
- Adversarial Robustness in Machine Learning (14 papers)Fault Detection and Control Systems (10 papers)Smart Grid Security and Resilience (5 papers)
- Journals
- ACM Transactions on Embedded Computing SystemsFormal Aspects of ComputingElectronic Proceedings in Theoretical Computer Science
- Partner nations
- United StatesDenmarkGermany
In The Last Decade
Diego Manzanas Lopez
17 papers receiving 123 citations
Peers
Comparison fields: 5 of 30
- Artificial Intelligence 92
- Control and Systems Engineering 45
- Software 24
- Electrical and Electronic Engineering 20
- Automotive Engineering 19
Countries citing papers authored by Diego Manzanas Lopez
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
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
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 9 | |
| 3 | 1 | |
| 4 | 9 | |
| 5 | 9 | |
| 6 | 7 | |
| 7 | 6 | |
| 8 | 6 | |
| 9 | 7 | |
| 10 | 7 | |
| 11 | 2 | |
| 12 | 6 | |
| 13 | 3 | |
| 14 | 7 | |
| 15 | 8 | |
| 16 | 26 | |
| 17 | 11 | |
| 18 | 0 |
About Diego Manzanas Lopez
Diego Manzanas Lopez is a scholar working on Control and Systems Engineering, Artificial Intelligence and Automotive Engineering, having authored 18 papers that have together received 125 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (14 papers), Fault Detection and Control Systems (10 papers) and Smart Grid Security and Resilience (5 papers). The work is most often cited by research in Software (24 citations), Artificial Intelligence (92 citations) and Control and Systems Engineering (45 citations). Diego Manzanas Lopez has collaborated with scholars based in United States, Denmark and Germany. Frequent co-authors include Taylor T. Johnson, Hoang-Dung Tran, Patrick Musau, Xiaodong Yang, Luan Viet Nguyen, Weiming Xiang, Nathaniel Hamilton, Christian Schilling, Stanley Bak and Matthias Althoff. Their work appears in journals such as ACM Transactions on Embedded Computing Systems, Formal Aspects of Computing and Electronic Proceedings in Theoretical Computer Science.
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.