Steve Harenberg
- Artificial Intelligence top 5%
- Statistical and Nonlinear Physics top 2%
- Computer Networks and Communications top 5%
- Information Systems
- Computer Vision and Pattern Recognition
- Co-authors
- Nagiza F. SamatovaStephen RanshousChristos FaloutsosShitian ShenDanai KoutraKshitij SharmaWen-Zhao ZhangSuren Byna
- Topics
- Complex Network Analysis Techniques (3 papers)Advanced Graph Neural Networks (3 papers)Advanced Data Storage Technologies (3 papers)
- Cited by
- Statistical and Nonlinear PhysicsComputational MathematicsComputer Networks and Communications
- Journals
- Journal of the Association for Information SystemsProcessesWiley Interdisciplinary Reviews Computational Statistics
- Partner nations
- United StatesGermany
In The Last Decade
Steve Harenberg
12 papers receiving 420 citations
Peers
Comparison fields: 5 of 69
- Artificial Intelligence 252
- Statistical and Nonlinear Physics 247
- Computer Networks and Communications 183
- Information Systems 42
- Computer Vision and Pattern Recognition 38
Countries citing papers authored by Steve Harenberg
This map shows the geographic impact of Steve Harenberg'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 Steve Harenberg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steve Harenberg more than expected).
Fields of papers citing papers by Steve Harenberg
This network shows the impact of papers produced by Steve Harenberg. 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 Steve Harenberg. The network helps show where Steve Harenberg may publish in the future.
Co-authorship network of co-authors of Steve Harenberg
This figure shows the co-authorship network connecting the top 25 collaborators of Steve Harenberg. A scholar is included among the top collaborators of Steve Harenberg 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 Steve Harenberg. Steve Harenberg 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 | Learning Contextual Embeddings for Knowledge Graph Completion | 5 |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 37 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 13 | |
| 9 | 4 | |
| 10 | 225 | |
| 11 | 2 | |
| 12 | 140 |
About Steve Harenberg
Steve Harenberg is a scholar working on Computer Graphics and Computer-Aided Design, Statistical and Nonlinear Physics and Artificial Intelligence, having authored 12 papers that have together received 434 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (3 papers), Advanced Graph Neural Networks (3 papers) and Advanced Data Storage Technologies (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (247 citations), Computational Mathematics (5 citations) and Computer Networks and Communications (183 citations). Steve Harenberg has collaborated with scholars based in United States and Germany. Frequent co-authors include Nagiza F. Samatova, Stephen Ranshous, Christos Faloutsos, Shitian Shen, Danai Koutra, Kshitij Sharma, Wen-Zhao Zhang, Suren Byna, Oliver Rübel and John Slankas. Their work appears in journals such as Journal of the Association for Information Systems, Processes and Wiley Interdisciplinary Reviews Computational Statistics.
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.