George Stantchev
Impact in
- Artificial Intelligence top 5%
- Wireless Signal Modulation Classification
- Internet Traffic Analysis and Secure E-voting
- Signal Processing top 10%
- Biometric Identification and Security
Papers in
-
- Speech and Audio Processing 2
- Co-authors
- Bryan NousainW. DorlandNail A. GumerovAmitabh VarshneyThomas M. AntonsenSimon J. CookeGreg McShaneWilliam M. Goldman
- Journals
- IEEE Transactions on Signal Processing (2 papers)Scientific Reports (1 paper)IEEE Journal of Selected Topics in Signal Processing (1 paper)Journal of Parallel and Distributed Computing (1 paper)Memoirs of the American Mathematical Society (1 paper)
- Partner nations
- United StatesFranceSingapore
In The Last Decade
George Stantchev
17 papers receiving 460 citations
Hit Papers
Peers
Comparison fields: 5 of 53
- Artificial Intelligence 342
- Signal Processing 93
- Aerospace Engineering 132
- Computer Vision and Pattern Recognition 91
- Electrical and Electronic Engineering 206
Countries citing papers authored by George Stantchev
This map shows the geographic impact of George Stantchev'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 George Stantchev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites George Stantchev more than expected).
Fields of papers citing papers by George Stantchev
This network shows the impact of papers produced by George Stantchev. 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 George Stantchev. The network helps show where George Stantchev may publish in the future.
Co-authorship network
The 20 scholars most cited alongside George Stantchev, 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 | 2024 | 0 | |
| 2 | 2021 | 4 | |
| 3 | 2020 | 3 | |
| 4 | 2019 | 1 | |
| 5 | 2018 | 1 | |
| 6 | Deep Learning for RF Device Fingerprinting in Cognitive Communication Networks Hit paper breakdown → | 2018 | 377 |
| 7 | 2018 | 1 | |
| 8 | 2017 | 0 | |
| 9 | 2016 | 2 | |
| 10 | 2016 | 10 | |
| 11 | 2016 | 1 | |
| 12 | 2015 | 2 | |
| 13 | 2015 | 2 | |
| 14 | 2014 | 5 | |
| 15 | 2013 | 1 | |
| 16 | 2011 | 0 | |
| 17 | 2010 | 1 | |
| 18 | 2009 | 6 | |
| 19 | 2008 | 63 | |
| 20 | 2008 | 0 |
About George Stantchev
George Stantchev is a scholar working on Signal Processing, Geometry and Topology, Nuclear and High Energy Physics, Atomic and Molecular Physics, and Optics and Computer Networks and Communications, having authored 21 papers that have together received 481 indexed citations. Recurring topics across this work include Gyrotron and Vacuum Electronics Research (6 papers), Electromagnetic Simulation and Numerical Methods (5 papers), Microwave Engineering and Waveguides (5 papers), Radio Frequency Integrated Circuit Design (3 papers), Advanced Data Storage Technologies (3 papers), Magnetic confinement fusion research (3 papers), Ionosphere and magnetosphere dynamics (2 papers) and Speech and Audio Processing (2 papers). The work is most often cited by research in Artificial Intelligence (342 citations), Signal Processing (93 citations), Aerospace Engineering (132 citations), Computer Vision and Pattern Recognition (91 citations) and Electrical and Electronic Engineering (206 citations). George Stantchev has collaborated with scholars based in United States, France and Singapore. Frequent co-authors include Bryan Nousain, W. Dorland, Nail A. Gumerov, Amitabh Varshney, Thomas M. Antonsen, Simon J. Cooke, Greg McShane, William M. Goldman, Ira B. Schwartz and John Petillo. Their work appears in journals such as IEEE Transactions on Signal Processing, Scientific Reports, IEEE Journal of Selected Topics in Signal Processing, Journal of Parallel and Distributed Computing and Memoirs of the American Mathematical Society.
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.