David J. Miller
- Artificial Intelligence top 1%
- Computer Networks and Communications top 2%
- Computer Vision and Pattern Recognition top 2%
- Signal Processing top 2%
- Electrical and Electronic Engineering top 10%
- Co-authors
- George KesidisKenneth RoseZhen XiangMoonseo ParkA. GershoA.V. RaoHaoti ZhongAnna Squicciarini
- Topics
- Anomaly Detection Techniques and Applications (26 papers)Neural Networks and Applications (25 papers)Adversarial Robustness in Machine Learning (20 papers)
- Partner nations
- United StatesItalyUnited Kingdom
In The Last Decade
David J. Miller
173 papers receiving 2.8k citations
Peers
Comparison fields: 5 of 158
- Artificial Intelligence 1.4k
- Computer Networks and Communications 748
- Computer Vision and Pattern Recognition 583
- Signal Processing 446
- Electrical and Electronic Engineering 326
Countries citing papers authored by David J. Miller
This map shows the geographic impact of David J. Miller'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 David J. Miller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David J. Miller more than expected).
Fields of papers citing papers by David J. Miller
This network shows the impact of papers produced by David J. Miller. 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 David J. Miller. The network helps show where David J. Miller may publish in the future.
Co-authorship network of co-authors of David J. Miller
This figure shows the co-authorship network connecting the top 25 collaborators of David J. Miller. A scholar is included among the top collaborators of David J. Miller 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 David J. Miller. David J. Miller is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 12 | |
| 3 | Graphical Time Warping for Joint Alignment of Multiple Curves | 2 |
| 4 | Content-driven detection of cyberbullying on the instagram social network | 84 |
| 5 | Parameter Selection Procedure for Signalized Arterial Simulation Calibration | 2 |
| 6 | Salting public traces with attack traffic to test flow classifiers | 23 |
| 7 | 31 | |
| 8 | 30 | |
| 9 | 68 | |
| 10 | Spectrum and Heat Kernel Asymptotics on General Laakso Spaces | 3 |
| 11 | 42 | |
| 12 | 13 | |
| 13 | 7 | |
| 14 | 5 | |
| 15 | 14 | |
| 16 | An Object-Based Metasystem for Distributed High Performance Simulation and Product Realization | 2 |
| 17 | A Mixture of Experts Classifier with Learning Based on Both Labelled and Unlabelled Data | 204 |
| 18 | An Information-theoretic Learning Algorithm for Neural Network Classification | 3 |
| 19 | 3 | |
| 20 | 7 |
About David J. Miller
David J. Miller is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition, having authored 187 papers that have together received 3.0k indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (26 papers), Neural Networks and Applications (25 papers) and Adversarial Robustness in Machine Learning (20 papers). The work is most often cited by research in Artificial Intelligence (1.4k citations), Signal Processing (446 citations) and Computer Networks and Communications (748 citations). David J. Miller has collaborated with scholars based in United States, Italy and United Kingdom. Frequent co-authors include George Kesidis, Kenneth Rose, Zhen Xiang, Moonseo Park, A. Gersho, A.V. Rao, Haoti Zhong, Anna Squicciarini, Tom Herbert and Hossein Soleimani. Their work appears in journals such as Bioinformatics, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine 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.