Chris Darken
Impact in
- Artificial Intelligence top 10%
- Neural Networks and Applications
- Fuzzy Logic and Control Systems
- Machine Learning and Algorithms
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- Face and Expression Recognition
- Image and Signal Denoising Methods
Papers in
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- Neural Networks and Applications 1
- Bayesian Modeling and Causal Inference 1
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- Face and Expression Recognition 1
- Co-authors
- John Moody (3 shared papers)J. Chang (1 shared paper)Eduardo D. Sontag (1 shared paper)M. J. Donahue (1 shared paper)Leonid Gurvits (1 shared paper)Lawrence I. Deckelbaum (1 shared paper)Kenneth M. O'Brien (1 shared paper)Mark L. Stetz (1 shared paper)
- Journals
- IEEE Transactions on Biomedical Engineering (1 paper)Constructive Approximation (1 paper)Neural Networks (1 paper)The Journal of Defense Modeling and Simulation Applications Methodology Technology (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (1 paper)
- Partner nations
- United StatesNorwayIndia
In The Last Decade
Chris Darken
10 papers receiving 334 citations
Peers
Comparison fields: 5 of 90
- Artificial Intelligence 170
- Computer Vision and Pattern Recognition 80
- Numerical Analysis 18
- Signal Processing 32
- Control and Systems Engineering 54
Countries citing papers authored by Chris Darken
This map shows the geographic impact of Chris Darken'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 Chris Darken with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris Darken more than expected).
Fields of papers citing papers by Chris Darken
This network shows the impact of papers produced by Chris Darken. 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 Chris Darken. The network helps show where Chris Darken may publish in the future.
Co-authors
The 23 scholars most cited alongside Chris Darken, 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 | 1990 | 118 | |
| 2 | 2003 | 116 | |
| 3 | 1997 | 65 | |
| 4 | 1991 | 21 | |
| 5 | 2003 | 11 | |
| 6 | 2020 | 9 | |
| 7 | New Generation of Instrumented Ranges: Enabling Automated Performance Analysis | 2009 | 6 |
| 8 | 2013 | 6 | |
| 9 | 1988 | 4 | |
| 10 | 2016 | 3 |
About Chris Darken
Chris Darken is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Surgery, Numerical Analysis and Mathematical Physics, having authored 10 papers that have together received 359 indexed citations. Recurring topics across this work include Coronary Interventions and Diagnostics (1 paper), Cardiac Imaging and Diagnostics (1 paper), Military Strategy and Technology (1 paper), Face and Expression Recognition (1 paper), Robotics and Sensor-Based Localization (1 paper), Indoor and Outdoor Localization Technologies (1 paper), Neural Networks and Applications (1 paper) and Bayesian Modeling and Causal Inference (1 paper). The work is most often cited by research in Artificial Intelligence (170 citations), Computer Vision and Pattern Recognition (80 citations), Numerical Analysis (18 citations), Signal Processing (32 citations) and Control and Systems Engineering (54 citations). Chris Darken has collaborated with scholars based in United States, Norway and India. Frequent co-authors include John Moody, J. Chang, Eduardo D. Sontag, M. J. Donahue, Leonid Gurvits, Lawrence I. Deckelbaum, Kenneth M. O'Brien, Mark L. Stetz, Gene Gindi and N.I. Santoso. Their work appears in journals such as IEEE Transactions on Biomedical Engineering, Constructive Approximation, Neural Networks, The Journal of Defense Modeling and Simulation Applications Methodology Technology and Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment.
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.