Matthew Rudary
- Artificial Intelligence top 10%
- Management Science and Operations Research top 10%
- Control and Systems Engineering
- Computer Vision and Pattern Recognition
- Management Information Systems
- Co-authors
- Satinder SinghM. R. JamesMartha E. PollackChristopher KiekintveldYevgeniy VorobeychikMichael P. WellmanVishal Dineshkumar SoniDavid Wingate
- Topics
- Bayesian Modeling and Causal Inference (3 papers)Fault Detection and Control Systems (2 papers)Target Tracking and Data Fusion in Sensor Networks (2 papers)
- Journals
- arXiv (Cornell University)International Conference on Automated Planning and SchedulingNeural Information Processing Systems
- Partner nations
- United States
In The Last Decade
Matthew Rudary
6 papers receiving 212 citations
Peers
Comparison fields: 5 of 53
- Artificial Intelligence 159
- Management Science and Operations Research 51
- Control and Systems Engineering 49
- Computer Vision and Pattern Recognition 32
- Management Information Systems 26
Countries citing papers authored by Matthew Rudary
This map shows the geographic impact of Matthew Rudary'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 Matthew Rudary with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Rudary more than expected).
Fields of papers citing papers by Matthew Rudary
This network shows the impact of papers produced by Matthew Rudary. 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 Matthew Rudary. The network helps show where Matthew Rudary may publish in the future.
Co-authorship network of co-authors of Matthew Rudary
This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Rudary. A scholar is included among the top collaborators of Matthew Rudary 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 Matthew Rudary. Matthew Rudary is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 6 | |
| 3 | 0 | |
| 4 | 130 | |
| 5 | Distributed feedback control for decision making on supply chains | 39 |
| 6 | 35 | |
| 7 | A Nonlinear Predictive State Representation | 19 |
About Matthew Rudary
Matthew Rudary is a scholar working on Artificial Intelligence, Management Information Systems and Marketing, having authored 7 papers that have together received 233 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (3 papers), Fault Detection and Control Systems (2 papers) and Target Tracking and Data Fusion in Sensor Networks (2 papers). The work is most often cited by research in Artificial Intelligence (159 citations), Management Science and Operations Research (51 citations) and Computational Mathematics (2 citations). Matthew Rudary has collaborated with scholars based in United States. Frequent co-authors include Satinder Singh, M. R. James, Satinder Singh, Martha E. Pollack, Christopher Kiekintveld, Yevgeniy Vorobeychik, Michael P. Wellman, Vishal Dineshkumar Soni, David Wingate and Deepak Khosla. Their work appears in journals such as arXiv (Cornell University), International Conference on Automated Planning and Scheduling and Neural Information Processing Systems.
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.