Research output per year
Research output per year
Personal profile
Research interests
- Model-based deep learning
- Wireless communications.
- Signal processing for communications.
- Information theory.
- Dual-function radar communications systems.
- Federated learning.
- Power line communications.
- Adaptive signal processing
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Dive into the research topics where Nir Shlezinger is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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CPDNet: Neural Online Error Monitoring for AI-Aided Kalman Filters
Zhang, W., Ni, X., Shlezinger, N. & Wang, Z., 1 Jan 2026, 14th IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2026. Institute of Electrical and Electronics Engineers, (Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Decentralized Multi-Channel MANET Power Optimization Using Graph Neural Networks
Alter, T., Shlezinger, N. & Segal, M., 1 Jan 2026, ICC 2026 - IEEE International Conference on Communications, Proceedings. Institute of Electrical and Electronics Engineers, (IEEE International Conference on Communications).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Deep Learning-Aided DoA Estimation with Uncertainty Extraction
Zohar, R., Ginzach, S. & Shlezinger, N., 1 Jan 2026, 14th IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2026. Institute of Electrical and Electronics Engineers, (Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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DeepNP: Deep Learning-Based Noise Prediction for Ultra-Reliable Low-Latency Communications
Waxman, A., Shlezinger, N. & Cohen, A., 1 Jan 2026, (Accepted/In press) In: IEEE Transactions on Vehicular Technology.Research output: Contribution to journal › Article › peer-review
Open Access -
Extremely Large-Scale Dynamic Metasurface Antennas for 6G Near-Field Networks: Opportunities and Challenges
Zhang, H., Shlezinger, N., Torcolacci, G., Guidi, F., Guerra, A., Yang, Q., Imani, M. F., Dardari, D. & Eldar, Y. C., 1 Jan 2026, (Accepted/In press) In: IEEE Vehicular Technology Magazine.Research output: Contribution to journal › Article › peer-review
Open Access -
Knowledge Distillation for Collaborative Learning in Distributed Communications and Sensing
Nguyen, N. T., Ma, M., Shlezinger, N., Choi, J., Eldar, Y. C., Swindlehurst, A. L. & Juntti, M., 1 Jan 2026, (Accepted/In press) In: IEEE Communications Magazine.Research output: Contribution to journal › Article › peer-review
1 Scopus citations -
Knowledge Distillation for Sensing-Assisted Long-Term Beam Tracking in mmWave Communications
Ma, M., Nguyen, N. T., Shlezinger, N., Eldar, Y. C., Lee Swindlehurst, A. & Juntti, M., 1 Jan 2026, In: IEEE Transactions on Wireless Communications. 25, p. 20494-20511 18 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Leaky Wave Antennas for Next-Generation Wireless Applications in Sub-THz Frequencies: Current Status and Research Challenges
Lang, N., Kludze, A. K., Shlezinger, N., Ghasempour, Y., Routtenberg, T., Alexandropoulos, G. C. & Eldar, Y. C., 1 Jan 2026, (Accepted/In press) In: IEEE Wireless Communications.Research output: Contribution to journal › Article › peer-review
1 Scopus citations -
Learning-Aided Privacy-Utility-Oriented Adaptive Rate Vector Quantization
Fishel, E., Bokobza, N., Shlomi, O. & Shlezinger, N., 1 Jan 2026, 14th IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2026. Institute of Electrical and Electronics Engineers, (Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Learning to Refine LLRs: Modular Neural Augmentation for MIMO-OFDM Receivers
Eger, O. & Shlezinger, N., 1 Jan 2026, ICC 2026 - IEEE International Conference on Communications, Proceedings. Institute of Electrical and Electronics Engineers, (IEEE International Conference on Communications).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Thesis
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Cyclostationary Signal Processing for Narrowband Power Line Communications
Shlezinger, N. (Author), Dabora, R. (Supervisor), 2017Student thesis: Doctoral Thesis
Press/Media
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Reports Summarize Engineering Research from Ben-Gurion University of the Negev (Memory-Efficient Distributed Unlearning)
9/03/26
1 item of Media coverage
Press/Media
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Findings from Ben-Gurion University of the Negev Provides New Data about Information Technology (Uncertainty-aware and Reliable Neural Mimo Receivers Via Modular Bayesian Deep Learning)
Shlezinger, N. & Raviv, T.
18/12/25
1 item of Media coverage
Press/Media
Projects
- 1 Active
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Adaptive, Lightweight, and Reliable AI-Aided Kalman Filters
Shlezinger, N. (PI)
1/01/25 → 31/12/28
Project: Research