Dr .Özlem Sabuncu |Blockchain-Driven Award |Best Researcher Award
Dr .Özlem Sabuncu ,Near East University,Turkey
🎓 Education and Academic Achievements:
Dr. Özlem Sabuncu, embarked on my academic journey with a Bachelor’s in Biomedical Engineering, later pursuing a Master’s in Electrical and Electronics Engineering. Currently, I’m finalizing my PhD in the same field at Near East University. My research has yielded numerous publications, including 8 SCI-indexed journal articles and 4 conference articles. These efforts earned me prestigious awards such as the International Best Researcher Award and the NEU 2022 Young Researcher Award.
🔬 Areas of Specialization :
- My expertise lies in Communication Systems and Optimization Theory, with a focus on enhancing network optimization.
🏆 Recognition and Awards:
I’ve been honored with the Best Paper Award at the IEEE International Conference on AI in Everything (AIE) – 2022, among other accolades.
💡 Contribution to Research & Development:
My work spans telecommunications, medical imaging, and blockchain technology. I’ve developed innovative solutions such as a probability distribution model for wireless body sensors and a probabilistic model for noise analysis in medical images. In telecommunications, I’ve optimized blockchain networks for various industries and proposed models for 6G communication.
🤝 Collaborations and Leadership:
I’ve organized 5 research conferences/workshops and engaged in 15 collaborative activities, showcasing my commitment to interdisciplinary research. As Deputy Chairman of the Department of Electrical and Electronics Engineering, I contribute to curricular development and academic leadership.,Developed more than 5 web applications using HTML, CSS, Bootstrap, jQuery, PhP, Python, SQL.
Publications:
General probability distribution model for wireless body sensors in the medical monitoring system
Effective deep learning classification for kidney stone using axial computed tomography (CT) images
Statistical RMS delay spread representation in 5G mm-Wave analysis using real-time measurements
Component-Related Phase Noise Evaluation Method for the LC Oscillators