Geoff Hulten
- Artificial Intelligence top 0.2%
- Signal Processing top 0.5%
- Computer Networks and Communications top 1%
- Information Systems top 1%
- Management Science and Operations Research top 2%
- Co-authors
- Pedro DomingosFang YuYinglian XieIvan OsipkovRina PanigrahyKannan AchanJavier HernandezZhengyou Zhang
- Topics
- Data Stream Mining Techniques (6 papers)Data Mining Algorithms and Applications (6 papers)Bayesian Modeling and Causal Inference (5 papers)
- Journals
- American Journal of Obstetrics and GynecologyACM SIGCOMM Computer Communication ReviewJournal of Computational and Graphical Statistics
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Geoff Hulten
19 papers receiving 3.0k citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Artificial Intelligence 2.8k
- Signal Processing 1.0k
- Computer Networks and Communications 923
- Information Systems 777
- Management Science and Operations Research 223
Countries citing papers authored by Geoff Hulten
This map shows the geographic impact of Geoff Hulten'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 Geoff Hulten with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Geoff Hulten more than expected).
Fields of papers citing papers by Geoff Hulten
This network shows the impact of papers produced by Geoff Hulten. 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 Geoff Hulten. The network helps show where Geoff Hulten may publish in the future.
Co-authorship network of co-authors of Geoff Hulten
This figure shows the co-authorship network connecting the top 25 collaborators of Geoff Hulten. A scholar is included among the top collaborators of Geoff Hulten 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 Geoff Hulten. Geoff Hulten 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 | 23 | |
| 3 | 61 | |
| 4 | 2 | |
| 5 | 99 | |
| 6 | 244 | |
| 7 | Learning at Low False Positive Rates. | 27 |
| 8 | Trends in Spam Products and Methods. | 19 |
| 9 | 17 | |
| 10 | Learning Bayesian Networks From Dependency Networks: A Preliminary Study | 14 |
| 11 | 102 | |
| 12 | Research on Statistical Relational Learning at the University of Washington | 1 |
| 13 | Mining Massive Relational Databases | 10 |
| 14 | 1 | |
| 15 | 47 | |
| 16 | A General Method for Scaling Up Machine Learning Algorithms and its Application to Clustering | 109 |
| 17 | Mining time-changing data streamsbreakdown → | 1073 |
| 18 | Catching up with the Data: Research Issues in Mining Data Streams. | 76 |
| 19 | Mining high-speed data streamsbreakdown → | 1298 |
About Geoff Hulten
Geoff Hulten is a scholar working on Signal Processing, Information Systems and Artificial Intelligence, having authored 19 papers that have together received 3.2k indexed citations. Recurring topics across this work include Data Stream Mining Techniques (6 papers), Data Mining Algorithms and Applications (6 papers) and Bayesian Modeling and Causal Inference (5 papers). The work is most often cited by research in Signal Processing (1.0k citations), Artificial Intelligence (2.8k citations) and Computer Networks and Communications (923 citations). Geoff Hulten has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Pedro Domingos, Fang Yu, Yinglian Xie, Ivan Osipkov, Rina Panigrahy, Kannan Achan, Javier Hernandez, Zhengyou Zhang, Zicheng Liu and Wen-tau Yih. Their work appears in journals such as American Journal of Obstetrics and Gynecology, ACM SIGCOMM Computer Communication Review and Journal of Computational and Graphical 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.