Chad Cumby
- Artificial Intelligence top 10%
- Information Systems top 5%
- Software top 10%
- Computer Networks and Communications
- Computer Science Applications top 10%
- Co-authors
- Dan RothRayid GhaniChen FuQing XieMark GrechanikCollin McMillanDenys PoshyvanykAndrew Fano
- Topics
- Software Engineering Research (3 papers)Cryptography and Data Security (2 papers)Privacy-Preserving Technologies in Data (2 papers)
- Journals
- International Conference on Machine LearningPrinciples of Knowledge Representation and ReasoningProceedings of the AAAI Conference on Artificial Intelligence
- Partner nations
- SwitzerlandUnited States
In The Last Decade
Chad Cumby
11 papers receiving 283 citations
Peers
Comparison fields: 5 of 37
- Artificial Intelligence 186
- Information Systems 164
- Software 39
- Computer Networks and Communications 35
- Computer Science Applications 32
Countries citing papers authored by Chad Cumby
This map shows the geographic impact of Chad Cumby'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 Chad Cumby with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chad Cumby more than expected).
Fields of papers citing papers by Chad Cumby
This network shows the impact of papers produced by Chad Cumby. 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 Chad Cumby. The network helps show where Chad Cumby may publish in the future.
Co-authorship network of co-authors of Chad Cumby
This figure shows the co-authorship network connecting the top 25 collaborators of Chad Cumby. A scholar is included among the top collaborators of Chad Cumby 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 Chad Cumby. Chad Cumby is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 29 | |
| 2 | 1 | |
| 3 | 103 | |
| 4 | 13 | |
| 5 | 14 | |
| 6 | 15 | |
| 7 | 23 | |
| 8 | On kernel methods for relational learning | 68 |
| 9 | Question-Answering via Enhanced Understanding of Questions. | 15 |
| 10 | Relational Representations that Facilitate Learning | 12 |
| 11 | SNoW User Guide | 15 |
About Chad Cumby
Chad Cumby is a scholar working on Software, Information Systems and Marketing, having authored 11 papers that have together received 308 indexed citations. Recurring topics across this work include Software Engineering Research (3 papers), Cryptography and Data Security (2 papers) and Privacy-Preserving Technologies in Data (2 papers). The work is most often cited by research in Software (39 citations), Information Systems (164 citations) and Computer Science Applications (32 citations). Chad Cumby has collaborated with scholars based in Switzerland and United States. Frequent co-authors include Dan Roth, Rayid Ghani, Chen Fu, Qing Xie, Mark Grechanik, Collin McMillan, Denys Poshyvanyk, Andrew Fano, Marko Krema and Andrew J. Carlson. Their work appears in journals such as International Conference on Machine Learning, Principles of Knowledge Representation and Reasoning and Proceedings of the AAAI Conference on Artificial Intelligence.
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.