Tyler Cody
Impact in
- Signal Processing top 10%
- Advanced Malware Detection Techniques
- Artificial Intelligence top 10%
- Reinforcement Learning in Robotics
- Imbalanced Data Classification Techniques
- Adversarial Robustness in Machine Learning
- Anomaly Detection Techniques and Applications
Papers in
- Software 4
-
- Advanced Malware Detection Techniques 8
- Co-authors
- Peter A. BelingStephen AdamsLaura FreemanPaul ParkAbdul Monem S. RahmaPaula J. DempseyLaura E. Beane FreemanAbdul Rahim Abdul Rahman
- Journals
- Computer (2 papers)Artificial Intelligence Review (1 paper)Journal of the Operational Research Society (1 paper)IEEE Systems Journal (1 paper)IEEE Instrumentation & Measurement Magazine (1 paper)
- Partner nations
- United StatesUkraine
In The Last Decade
Tyler Cody
33 papers receiving 260 citations
Peers
Comparison fields: 5 of 72
- Signal Processing 59
- Artificial Intelligence 133
- Software 15
- Computer Networks and Communications 54
- Management Science and Operations Research 29
Countries citing papers authored by Tyler Cody
This map shows the geographic impact of Tyler Cody'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 Tyler Cody with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tyler Cody more than expected).
Fields of papers citing papers by Tyler Cody
This network shows the impact of papers produced by Tyler Cody. 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 Tyler Cody. The network helps show where Tyler Cody may publish in the future.
Co-authorship network
The 21 scholars most cited alongside Tyler Cody, 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 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 3 | |
| 6 | 2023 | 2 | |
| 7 | 2023 | 1 | |
| 8 | 2023 | 1 | |
| 9 | 2023 | 4 | |
| 10 | 2023 | 5 | |
| 11 | 2022 | 3 | |
| 12 | 2022 | 58 | |
| 13 | 2022 | 1 | |
| 14 | 2022 | 3 | |
| 15 | 2022 | 6 | |
| 16 | 2022 | 16 | |
| 17 | 2022 | 5 | |
| 18 | 2021 | 4 | |
| 19 | 2021 | 22 | |
| 20 | 2020 | 6 |
About Tyler Cody
Tyler Cody is a scholar working on Software, Signal Processing, Artificial Intelligence, Control and Systems Engineering and Computer Networks and Communications, having authored 40 papers that have together received 265 indexed citations. Recurring topics across this work include Fault Detection and Control Systems (9 papers), Advanced Malware Detection Techniques (8 papers), Network Security and Intrusion Detection (7 papers), Machine Learning and Algorithms (6 papers), Adversarial Robustness in Machine Learning (6 papers), Information and Cyber Security (6 papers), Machine Fault Diagnosis Techniques (5 papers) and Imbalanced Data Classification Techniques (4 papers). The work is most often cited by research in Signal Processing (59 citations), Artificial Intelligence (133 citations), Software (15 citations), Computer Networks and Communications (54 citations) and Management Science and Operations Research (29 citations). Tyler Cody has collaborated with scholars based in United States and Ukraine. Frequent co-authors include Peter A. Beling, Stephen Adams, Laura Freeman, Paul Park, Abdul Monem S. Rahma, Paula J. Dempsey, Laura E. Beane Freeman, Abdul Rahim Abdul Rahman, Alejandro Salado and Lanxiao Huang. Their work appears in journals such as Computer, Artificial Intelligence Review, Journal of the Operational Research Society, IEEE Systems Journal and IEEE Instrumentation & Measurement Magazine.
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.