Steve Harenberg
-
- Complex Network Analysis Techniques 3
-
- Advanced Data Storage Technologies 3
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks 3
- Topic Modeling 2
- Data Stream Mining Techniques 2
- Anomaly Detection Techniques and Applications 2
-
- Data Management and Algorithms 1
-
- Bioinformatics and Genomic Networks 2
- Co-authors
- Nagiza F. SamatovaStephen RanshousChristos FaloutsosShitian ShenDanai KoutraKshitij SharmaWen-Zhao ZhangSuren Byna
- Cited by
- Statistical and Nonlinear PhysicsComputational MathematicsComputer Networks and Communications
- Journals
- Wiley Interdisciplinary Reviews Computational Statistics (2 papers)Statistical Analysis and Data Mining The ASA Data Science Journal (1 paper)Journal of the Association for Information Systems (1 paper)
- Partner nations
- United StatesGermany
In The Last Decade
Steve Harenberg
12 papers receiving 420 citations
Peers
Comparison fields: 5 of 69
- Statistical and Nonlinear Physics 247
- Computational Mathematics 5
- Computer Networks and Communications 183
- Artificial Intelligence 252
- Signal Processing 36
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
The 25 scholars most cited alongside Steve Harenberg, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 1 | |
| 2 | Learning Contextual Embeddings for Knowledge Graph Completion | 2017 | 5 |
| 3 | 2017 | 1 | |
| 4 | 2017 | 3 | |
| 5 | 2016 | 37 | |
| 6 | 2016 | 1 | |
| 7 | 2016 | 2 | |
| 8 | 2016 | 13 | |
| 9 | 2016 | 4 | |
| 10 | 2015 | 225 | |
| 11 | 2014 | 2 | |
| 12 | 2014 | 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), Advanced Data Storage Technologies (3 papers), Bioinformatics and Genomic Networks (2 papers), Topic Modeling (2 papers), Data Stream Mining Techniques (2 papers), Anomaly Detection Techniques and Applications (2 papers) and Data Management and Algorithms (1 paper). 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 Wiley Interdisciplinary Reviews Computational Statistics, Statistical Analysis and Data Mining The ASA Data Science Journal, Journal of the Association for Information Systems, Processes and OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).
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.