Carla E. Brodley
Impact in
- Artificial Intelligence top 0.1%
- Machine Learning and Data Classification
- Anomaly Detection Techniques and Applications
- Advanced Clustering Algorithms Research
- Signal Processing top 0.2%
- Advanced Malware Detection Techniques
Papers in
-
- Machine Learning and Data Classification 20
- Anomaly Detection Techniques and Applications 15
- Imbalanced Data Classification Techniques 14
- Machine Learning and Algorithms 12
- Co-authors
- M. A. FriedlJennifer DyXiaoli Z. FernTerran LanePaul E. UtgoffByron WallaceThomas A TrikalinosAndrea Danyluk
- Journals
- Machine Learning (7 papers)Communications of the ACM (5 papers)Computer Vision and Image Understanding (3 papers)American Scientist (3 papers)ACM Transactions on Information and System Security (2 papers)
- Partner nations
- United StatesMexicoFrance
In The Last Decade
Carla E. Brodley
129 papers receiving 9.0k citations
Hit Papers
Peers
Comparison fields: 5 of 212
- Artificial Intelligence 5.0k
- Signal Processing 1.5k
- Computer Vision and Pattern Recognition 2.4k
- Media Technology 649
- Information Systems 1.4k
Countries citing papers authored by Carla E. Brodley
This map shows the geographic impact of Carla E. Brodley'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 Carla E. Brodley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carla E. Brodley more than expected).
Fields of papers citing papers by Carla E. Brodley
This network shows the impact of papers produced by Carla E. Brodley. 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 Carla E. Brodley. The network helps show where Carla E. Brodley may publish in the future.
Co-authors
The 25 scholars most cited alongside Carla E. Brodley, 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 | 2025 | 0 | |
| 2 | 2024 | 6 | |
| 3 | A Quantitative Machine Learning Approach to Master Students Admission for Professional Institutions. | 2020 | 4 |
| 4 | Decrypting cryptogenic epilepsy: semi-supervised hierarchical conditional random fields for detecting cortical lesions in MRI-negative patients | 2016 | 7 |
| 5 | Hierarchical Conditional Random Fields for Outlier Detection: An Application to Detecting Epileptogenic Cortical Malformations | 2014 | 9 |
| 6 | The Constrained Weight Space SVM: Learning with Ranked Features | 2011 | 28 |
| 7 | Spam Filtering Using Inexact String Matching in Explicit Feature Space with On-Line Linear Classifiers. | 2006 | 28 |
| 8 | Proceedings of the twenty-first international conference on Machine learning Hit paper breakdown → | 2004 | 847 |
| 9 | Feature Selection for Unsupervised Learning Hit paper breakdown → | 2004 | 657 |
| 10 | User re-authentication via mouse movements | 2004 | 3 |
| 11 | Proceedings of the 2004 ACM workshop on Visualization and data mining for computer security | 2004 | 35 |
| 12 | Boosting lazy decision trees | 2003 | 11 |
| 13 | Random projection for high dimensional data clustering: a cluster ensemble approach | 2003 | 379 |
| 14 | Feature Subset Selection and Order Identification for Unsupervised Learning | 2000 | 164 |
| 15 | Data Reduction Techniques for Instance-Based Learning from Human/Computer Interface Data | 2000 | 4 |
| 16 | A Hybrid Lazy-Eager Approach to Reducing the Computation and Memory Requirements of Local Parametric Learning Algorithms | 1999 | 1 |
| 17 | Image feature reduction through spoiling: its application to multiple matched filters for focus of attention | 1997 | 3 |
| 18 | Learning to Schedule Straight-Line Code | 1997 | 42 |
| 19 | Comparison of regression methods, symbolic induction methods and neural networks in morbidity diagnosis and mortality prediction in equine gastrointestinal colic | 1996 | 1 |
| 20 | Identifying and eliminating mislabeled training instances | 1996 | 138 |
About Carla E. Brodley
Carla E. Brodley is a scholar working on Artificial Intelligence, Computer Science Applications, Signal Processing, Computer Vision and Pattern Recognition and Information Systems, having authored 132 papers that have together received 9.8k indexed citations. Recurring topics across this work include Machine Learning and Data Classification (20 papers), Image Retrieval and Classification Techniques (16 papers), Data Mining Algorithms and Applications (15 papers), Anomaly Detection Techniques and Applications (15 papers), Network Security and Intrusion Detection (14 papers), Imbalanced Data Classification Techniques (14 papers), Machine Learning and Algorithms (12 papers) and Advanced Image and Video Retrieval Techniques (12 papers). The work is most often cited by research in Artificial Intelligence (5.0k citations), Signal Processing (1.5k citations), Computer Vision and Pattern Recognition (2.4k citations), Media Technology (649 citations) and Information Systems (1.4k citations). Carla E. Brodley has collaborated with scholars based in United States, Mexico and France. Frequent co-authors include M. A. Friedl, Jennifer Dy, Xiaoli Z. Fern, Terran Lane, Paul E. Utgoff, Byron Wallace, Thomas A Trikalinos, Andrea Danyluk, Kevin Small and Joseph Lau. Their work appears in journals such as Machine Learning, Communications of the ACM, Computer Vision and Image Understanding, American Scientist and ACM Transactions on Information and System Security.
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.