Maher Nouiehed
- Artificial Intelligence top 10%
- Computer Networks and Communications
- Computational Mechanics
- Electrical and Electronic Engineering
- Aerospace Engineering
- Co-authors
- Meisam RazaviyaynMaziar SanjabiMingyi HongSongtao LuRaed Al KontarJason D. LeeJong‐Shi PangMosharaf Chowdhury
- Topics
- Stochastic Gradient Optimization Techniques (3 papers)Sparse and Compressive Sensing Techniques (2 papers)Privacy-Preserving Technologies in Data (2 papers)
- Journals
- IEEE AccessIEEE Signal Processing MagazineIEEE Transactions on Neural Networks and Learning Systems
- Partner nations
- United StatesLebanonSingapore
In The Last Decade
Maher Nouiehed
8 papers receiving 178 citations
Peers
Comparison fields: 5 of 47
- Artificial Intelligence 99
- Computer Networks and Communications 36
- Computational Mechanics 28
- Electrical and Electronic Engineering 27
- Aerospace Engineering 22
Countries citing papers authored by Maher Nouiehed
This map shows the geographic impact of Maher Nouiehed'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 Maher Nouiehed with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maher Nouiehed more than expected).
Fields of papers citing papers by Maher Nouiehed
This network shows the impact of papers produced by Maher Nouiehed. 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 Maher Nouiehed. The network helps show where Maher Nouiehed may publish in the future.
Co-authorship network of co-authors of Maher Nouiehed
This figure shows the co-authorship network connecting the top 25 collaborators of Maher Nouiehed. A scholar is included among the top collaborators of Maher Nouiehed 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 Maher Nouiehed. Maher Nouiehed is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 3 | |
| 3 | 19 | |
| 4 | 37 | |
| 5 | 66 | |
| 6 | Solving a class of non-convex min-max games using iterative first order methods | 36 |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 12 | |
| 10 | 5 |
About Maher Nouiehed
Maher Nouiehed is a scholar working on Management Science and Operations Research, Artificial Intelligence and Computer Science Applications, having authored 10 papers that have together received 180 indexed citations. Recurring topics across this work include Stochastic Gradient Optimization Techniques (3 papers), Sparse and Compressive Sensing Techniques (2 papers) and Privacy-Preserving Technologies in Data (2 papers). The work is most often cited by research in Computational Mathematics (3 citations), Artificial Intelligence (99 citations) and Numerical Analysis (12 citations). Maher Nouiehed has collaborated with scholars based in United States, Lebanon and Singapore. Frequent co-authors include Meisam Razaviyayn, Maziar Sanjabi, Mingyi Hong, Songtao Lu, Raed Al Kontar, Jason D. Lee, Jong‐Shi Pang, Mosharaf Chowdhury, Jionghua Jin and Garvesh Raskutti. Their work appears in journals such as IEEE Access, IEEE Signal Processing Magazine and IEEE Transactions on Neural Networks and Learning Systems.
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.