Galileo Namata
- Artificial Intelligence top 0.5%
- Statistical and Nonlinear Physics top 0.5%
- Computer Vision and Pattern Recognition top 2%
- Information Systems top 2%
- Computer Networks and Communications top 5%
- Co-authors
- Lise GetoorMustafa BilgicTina Eliassi‐RadBrian GallagherPrithviraj SenChristopher DiehlBen LondonBert Huang
- Topics
- Complex Network Analysis Techniques (10 papers)Data Quality and Management (7 papers)Advanced Graph Neural Networks (5 papers)
- Journals
- AI MagazineACM Transactions on Knowledge Discovery from DataCold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory)
- Partner nations
- United States
In The Last Decade
Galileo Namata
18 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 92
- Artificial Intelligence 2.0k
- Statistical and Nonlinear Physics 908
- Computer Vision and Pattern Recognition 460
- Information Systems 393
- Computer Networks and Communications 202
Countries citing papers authored by Galileo Namata
This map shows the geographic impact of Galileo Namata'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 Galileo Namata with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Galileo Namata more than expected).
Fields of papers citing papers by Galileo Namata
This network shows the impact of papers produced by Galileo Namata. 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 Galileo Namata. The network helps show where Galileo Namata may publish in the future.
Co-authorship network of co-authors of Galileo Namata
This figure shows the co-authorship network connecting the top 25 collaborators of Galileo Namata. A scholar is included among the top collaborators of Galileo Namata 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 Galileo Namata. Galileo Namata is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | Query-driven active surveying for collective classification | 100 |
| 3 | 8 | |
| 4 | 10 | |
| 5 | 23 | |
| 6 | 4 | |
| 7 | A Pipeline Approach to Graph Identification | 1 |
| 8 | 4 | |
| 9 | 58 | |
| 10 | 21 | |
| 11 | Resolving Personal Names in Email Using Context Expansion | 19 |
| 12 | Collective Classi!cation in Network Data | 4 |
| 13 | Collective Classification in Network Databreakdown → | 1830 |
| 14 | Relationship identification for social network discovery | 65 |
| 15 | 100 | |
| 16 | 21 | |
| 17 | 6 | |
| 18 | 25 |
About Galileo Namata
Galileo Namata is a scholar working on Statistical and Nonlinear Physics, Management Science and Operations Research and Artificial Intelligence, having authored 18 papers that have together received 2.3k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (10 papers), Data Quality and Management (7 papers) and Advanced Graph Neural Networks (5 papers). The work is most often cited by research in Statistical and Nonlinear Physics (908 citations), Artificial Intelligence (2.0k citations) and Computational Mathematics (15 citations). Galileo Namata has collaborated with scholars based in United States. Frequent co-authors include Lise Getoor, Mustafa Bilgic, Tina Eliassi‐Rad, Brian Gallagher, Prithviraj Sen, Christopher Diehl, Ben London, Bert Huang, Swapna Somasundaran and Janyce Wiebe. Their work appears in journals such as AI Magazine, ACM Transactions on Knowledge Discovery from Data and Cold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory).
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.