Innovative Research Award
| Wurod Mohamed |
| Affiliation |
University of Arkansas at Little Rock |
| Country |
United States |
| Scopus ID |
57204874896 |
| Documents |
12 |
| Citations |
30 |
| h-index |
3 |
| Subject Area |
Engineering |
| Event |
Global Innovation Technologist Awards |
| ORCID |
0000-0003-2421-1534 |
Wurod Mohamed
University of Arkansas at Little Rock, United States
Wurod Mohamed is an engineering researcher whose scholarly work focuses on wireless communication systems, signal processing, antenna characterization, electromagnetic modeling, and intelligent communication technologies. Her publications demonstrate continued contributions to millimeter-wave communications, audio transmission enhancement, radar cross-section analysis, and image transmission techniques. The research portfolio reflects interdisciplinary engineering applications supported by computational methods and practical system evaluation, making it relevant to modern wireless infrastructure and emerging communication technologies.[1]
Abstract
The research activities of Wurod Mohamed emphasize engineering solutions for next-generation communication systems through analytical modeling, artificial intelligence, and electromagnetic simulation. Her work addresses practical challenges involving direction-of-arrival estimation, wireless propagation, radar characterization, multimedia transmission, and signal reliability. Publications appearing in recognized engineering journals and conference proceedings demonstrate a balanced combination of theoretical development and practical validation. Collectively, these studies contribute to the advancement of communication system efficiency and electromagnetic engineering while supporting innovation within modern wireless technologies.[2]
Keywords
Wireless Communications, Engineering, Deep Learning, Electromagnetic Modeling, Millimeter-Wave Systems, Signal Processing, Artificial Intelligence, Radar Cross Section.
Introduction
Engineering research increasingly relies on intelligent computational methods to improve communication performance under complex operating conditions. Wurod Mohamed’s scholarly work follows this direction by integrating signal processing algorithms, electromagnetic analysis, and deep learning techniques into communication system design. Her studies illustrate practical engineering approaches that improve estimation accuracy, transmission quality, and propagation modeling across multiple communication environments.[3]
Research Profile
According to the available scholarly profile, the researcher has authored 12 indexed publications with 30 citations and an h-index of 3. The publication record demonstrates sustained engagement in engineering research, particularly wireless communication, antenna systems, artificial intelligence applications, and computational electromagnetic analysis. These contributions indicate active participation in internationally indexed scientific literature.[1]
Research Contributions
- Development of deep learning-based electromagnetic frameworks for millimeter-wave direction-of-arrival estimation.
- Research on LMMSE-based enhancement of audio transmission performance.
- Analysis of shadow path loss models considering antenna gain effects.
- Image transmission optimization using advanced interleaving techniques.
- Evaluation of bistatic and monostatic radar cross-section characteristics.
Publications
- Deep Learning-Based Rigorous Electromagnetic Framework for Direction of Arrival Estimation in Millimeter-Wave Communication Systems Based on Embedded Radiation Patterns, Electronics (2026).
- Performance Enhancement of Audio Transmission Based on LMMSE Method, Indonesian Journal of Electrical Engineering and Computer Science (2021).
- Factors Influencing the Shadow Path Loss Model with Different Antenna Gains over Large-Scale Fading Channel, AIMS 2021.
- New 2-D Interleaving Grouping LBC Applied on Image Transmission, International Journal of Electrical and Computer Engineering (2021).
- Evaluation of Bistatic and Monostatic RCS for Simple and Complex Targets in X-Band, International Journal of Microwave and Optical Technology (2020).
Research Impact
The research portfolio demonstrates measurable scholarly visibility through indexed publications and citations while addressing technically significant engineering topics. The combination of wireless communications, artificial intelligence, and electromagnetic analysis reflects emerging priorities within communication engineering. The work contributes to improving communication reliability, signal estimation, and computational modeling for practical engineering applications.[4]
Award Suitability
Considering the documented publication record, engineering specialization, and continuing research activity, Wurod Mohamed demonstrates characteristics consistent with recognition by the Global Innovation Technologist Awards. The portfolio illustrates innovation in communication engineering, interdisciplinary application of computational intelligence, and contributions that align with technological advancement and scientific dissemination. The evaluation is based upon publicly available scholarly information and indexed research outputs.[5]
Conclusion
Wurod Mohamed has established a research profile centered on engineering innovation in wireless communications, signal processing, and computational electromagnetics. Through peer-reviewed publications and conference contributions, the researcher has addressed practical communication challenges using analytical and artificial intelligence-based approaches. The documented scholarly record supports recognition within academic engineering communities while demonstrating continuing engagement in research relevant to future communication technologies.
External Links
References
- Elsevier. (n.d.). Scopus Author Details: Wurod Mohamed, Author ID 57204874896.
https://www.scopus.com/authid/detail.uri?authorId=57204874896
- Mohamed, W. (2026). Deep Learning-Based Rigorous Electromagnetic Framework… Electronics.
https://doi.org/10.3390/electronics15132934
- Mohamed, W. (2021). Performance Enhancement of Audio Transmission Based on LMMSE Method.
https://doi.org/10.11591/ijeecs.v21.i2.pp903-910
- IEEE. (2021). Factors Influencing the Shadow Path Loss Model with Different Antenna Gains over Large-Scale Fading Channel.
https://doi.org/10.1109/AIMS52415.2021.9466043
- Global Innovation Technologist Awards. (n.d.). Official Award Website.
innovationtechnologist.com