Syed Ghazi Sarwat
- Electrical and Electronic Engineering top 10%
- Materials Chemistry top 10%
- Mechanical Engineering
- Artificial Intelligence top 10%
- Cellular and Molecular Neuroscience
- Co-authors
- Harish BhaskaranJamie H. WarnerK.R. RaviAbu SebastianTimoleon MoraitisBenedikt KerstingVara Prasad JonnalagaddaC. David Wright
- Topics
- Advanced Memory and Neural Computing (16 papers)Phase-change materials and chalcogenides (13 papers)Neural Networks and Reservoir Computing (8 papers)
- Partner nations
- SwitzerlandUnited KingdomUnited States
In The Last Decade
Syed Ghazi Sarwat
34 papers receiving 726 citations
Peers
Comparison fields: 5 of 54
- Electrical and Electronic Engineering 445
- Materials Chemistry 400
- Mechanical Engineering 137
- Artificial Intelligence 120
- Cellular and Molecular Neuroscience 78
Countries citing papers authored by Syed Ghazi Sarwat
This map shows the geographic impact of Syed Ghazi Sarwat'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 Syed Ghazi Sarwat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Syed Ghazi Sarwat more than expected).
Fields of papers citing papers by Syed Ghazi Sarwat
This network shows the impact of papers produced by Syed Ghazi Sarwat. 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 Syed Ghazi Sarwat. The network helps show where Syed Ghazi Sarwat may publish in the future.
Co-authorship network of co-authors of Syed Ghazi Sarwat
This figure shows the co-authorship network connecting the top 25 collaborators of Syed Ghazi Sarwat. A scholar is included among the top collaborators of Syed Ghazi Sarwat 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 Syed Ghazi Sarwat. Syed Ghazi Sarwat is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 4 | |
| 6 | 2 | |
| 7 | 5 | |
| 8 | 36 | |
| 9 | 48 | |
| 10 | 90 | |
| 11 | 12 | |
| 12 | 1 | |
| 13 | 13 | |
| 14 | 13 | |
| 15 | 20 | |
| 16 | 23 | |
| 17 | 18 | |
| 18 | 21 | |
| 19 | 34 | |
| 20 | 18 |
About Syed Ghazi Sarwat
Syed Ghazi Sarwat is a scholar working on Materials Chemistry, Metals and Alloys and Electrical and Electronic Engineering, having authored 35 papers that have together received 750 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (16 papers), Phase-change materials and chalcogenides (13 papers) and Neural Networks and Reservoir Computing (8 papers). The work is most often cited by research in Materials Chemistry (400 citations), Electrical and Electronic Engineering (445 citations) and Polymers and Plastics (64 citations). Syed Ghazi Sarwat has collaborated with scholars based in Switzerland, United Kingdom and United States. Frequent co-authors include Harish Bhaskaran, Jamie H. Warner, K.R. Ravi, Abu Sebastian, Timoleon Moraitis, Benedikt Kersting, Vara Prasad Jonnalagadda, C. David Wright, Yingqiu Zhou and Baldev Raj. Their work appears in journals such as Nature, Chemical Reviews and Advanced Materials.
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.