Neil Shah
- Artificial Intelligence top 1%
- Information Systems top 2%
- Computer Networks and Communications top 5%
- Signal Processing top 2%
- Statistical and Nonlinear Physics top 2%
- Co-authors
- Christos FaloutsosAlex BeutelMeet SoniYozen LiuHemant A. PatilBrian GallagherTong ZhaoManan Shah
- Topics
- Advanced Graph Neural Networks (19 papers)Recommender Systems and Techniques (16 papers)Complex Network Analysis Techniques (14 papers)
- Journals
- SHILAP Revista de lepidopterologíaComputers in Human BehaviorIEEE Transactions on Neural Networks and Learning Systems
- Partner nations
- United StatesIndiaChina
In The Last Decade
Neil Shah
59 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 110
- Artificial Intelligence 933
- Information Systems 343
- Computer Networks and Communications 305
- Signal Processing 304
- Statistical and Nonlinear Physics 285
Countries citing papers authored by Neil Shah
This map shows the geographic impact of Neil Shah'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 Neil Shah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Neil Shah more than expected).
Fields of papers citing papers by Neil Shah
This network shows the impact of papers produced by Neil Shah. 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 Neil Shah. The network helps show where Neil Shah may publish in the future.
Co-authorship network of co-authors of Neil Shah
This figure shows the co-authorship network connecting the top 25 collaborators of Neil Shah. A scholar is included among the top collaborators of Neil Shah 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 Neil Shah. Neil Shah 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 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 0 | |
| 12 | 5 | |
| 13 | 2 | |
| 14 | 2 | |
| 15 | 5 | |
| 16 | 34 | |
| 17 | 91 | |
| 18 | 140 | |
| 19 | On Summarizing Large-Scale Dynamic Graphs. | 8 |
| 20 | 85 |
About Neil Shah
Neil Shah is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Information Systems, having authored 69 papers that have together received 1.4k indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (19 papers), Recommender Systems and Techniques (16 papers) and Complex Network Analysis Techniques (14 papers). The work is most often cited by research in Computational Mathematics (19 citations), Artificial Intelligence (933 citations) and Signal Processing (304 citations). Neil Shah has collaborated with scholars based in United States, India and China. Frequent co-authors include Christos Faloutsos, Alex Beutel, Meet Soni, Yozen Liu, Hemant A. Patil, Brian Gallagher, Tong Zhao, Manan Shah, Meng Jiang and Bryan Hooi. Their work appears in journals such as SHILAP Revista de lepidopterología, Computers in Human Behavior 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.