News

September

• Our recent work on deep unfolding with approximated computations for rapid optimization is now available on Arxiv.

August

• I am extremely honored to receive the 2025 IEEE Communications Society Marconi prize, an award granted annually recognizing a article of notable contribution in the area of wireless communications, for our article on beam focusing for multi-user communications, published in the IEEE Transactions on Wireless Communications on September 2022.

• The following journal paper was accepted for publication:

Z. Davidov, A. Osovizky, N. Shlezinger, and M. Ghelman, "A Compton Camera Resolution Enhancement by Increasing the Number of Sensors per Readout Channel", accepted to the IEEE Transactions on Nuclear Sciences, 2025.

July

• I am honored to receive the Israel Science Foundation Personal grant for my research on adaptive AI-aided Kalman filters.

• Our recent work on sparsity-aware extended Kalman filters for tracking dynamic graph topologies is now available on Arxiv.

• The following journal paper was accepted for publication:

E. Fishel, M. Malka, S. Ginzach, and N. Shlezinger, "Remote Inference over Dynamic Links via Adaptive Rate Deep Task-Oriented Vector Quantization", accepted to the IEEE Transactions on Signal Processing, 2025. 

June

• Our new work on online learned adaptive lattice quantizers is now available on Arxiv.

• The following journal papers were accepted for publication:

T. Raviv, S. Park, O. Simeone, and N. Shlezinger, "Uncertainty-Aware and Reliable Neural MIMO Receivers via Modular Bayesian Deep Learning",  accepted to the IEEE Transactions on Vehicular Technology, 2025.

Y. Dahan, G. Revach, J. Dunik, and N. Shlezinger, "Bayesian KalmanNet: Quantifying Uncertainty in Deep Learning Augmented Kalman Filter", accepted to the IEEE Transactions on Signal Processing, 2025.

May

• The results for IEEE SPAWC 2025 are in. This year (like last year) we will be presenting three papers from our group, in deep learning for remote inference, AI-aided optimization, and multiuser localization. 

• Our recent paper on the adversarial vulnerability of iterative optimizers is up on Arxiv.

• Our new work on memory efficient distributed unlearning can be found online.

April

• Our new paper on AI-aided subspace methods for near-field localization can be found on Arxiv.

• The following journal papers were accepted for publication:

N. Lang, N. Shlezinger, R. G. L. D'Oliveira, and S. El Rouayheb,  "Compressed Private Aggregation for Scalable and Robust Federated Learning over Massive Networks", accepted to the IEEE Transactions on Mobile Computing,  2025.

N. Shlezinger, G. Revach, A. Ghosh, S. Chatterjee, S. Tang, T. Imbiriba, J. Dunik, O. Straka, P. Closas, and Y. C. Eldar, "AI-Aided Kalman Filters", accepted to the IEEE  Signal Processing Magazine, 2025.

March

• Our recent work  on privacy-aware user selection for federated learning is now available on Arxiv.

• The following journal papers were accepted for publication:

Q. Yang, A. Guerra, F. Guidi, N. Shlezinger, H. Zhang, D. Dardari, B. Wang, and Y. C. Eldar, "Beam Focusing for Near-Field Multi-User Localization",  accepted to the IEEE Transactions on Vehicular Technology, 2025.

H. Zhang, N. Shlezinger, F. Guidi, A. Guerra, D. Dardari, M. F. Imani, and Y. C. Eldar, "Near-Field Beam-Focusing for Wireless Power Transfer with Dynamic Metasurface Antennas", accepted to the IEEE Internet of Things Journal, 2025.

T. Alter and N. Shlezinger, "Rapid Optimization of Superposition Codes for Multi-Hop NOMA MANETs via Deep Unfolding",  accepted to the IEEE Transactions on Communications, 2025

February

• The following journal papers were accepted for publication:

L. M. Schmid, T. Raviv, N. Shlezinger, and L. Schmalen, "Blind Channel Estimation and Joint Symbol Detection with Data-Driven Factor Graphs",  accepted to the IEEE Transactions on Communications, 2025.

O. Levy and N. Shlezinger, "Rapid and Power-Aware Learned Optimization for Modular Receive Beamforming", accepted to the IEEE Transactions on Communications, 2025.

T. Vol, L. Danial, and N. Shlezinger, "Learning Task-Based Trainable Neuromorphic ADCs via Power-Aware Distillation", accepted to the IEEE Transactions on Signal Processing, 2025.

January

• Our recent work on AI-based rate-adaptive task-based vector quantization is now available on Arxiv.

• The following journal paper was accepted for publication:

N. Uzlaner, T. Raviv, N. Shlezinger, and K. Todros, "Asynchronous Online Adaptation via Modular Drift Detection for Deep Receivers",  accepted to the IEEE Transactions on Wireless Communications, 2025

December

• I am greatly honored to be a co-author of a work that is the recipient of the IEEE Signal Processing Society Young Author Best Paper Award 2025, for the paper "Joint Transmit Beamforming for Multiuser MIMO Communications and MIMO Radar", published in the  June 2020 edition of the IEEE Transactions on Signal Processing!

• ICASSP 2025 results have arrived. This year I am co-authoring 8 different papers, 6 of which from our group, all in topics which I am particularly excited about, including the integration of AI with wireless receivers, dynamic systems, array signal processing, distributed systems, and optimization. 

• The following journal papers were accepted for publication:

I. Nuri and N. Shlezinger, "Learning Flock: Enhancing Sets of Particles for Multi Sub-State Particle Filtering with Neural Augmentation",  accepted to the IEEE Transactions on Signal Processing, 2024.

J. Chen, Y. Fang, A. Khisti, A. Ozgur, N. Shlezinger, and C. Tian, "Information Compression in the AI Era: Recent Advances and Future Challenges", accepted to the IEEE  Journal on Selected Areas in Communications, 2024.

November

• The following journal papers were accepted for publication:

D. H. Shmuel, J. P, Merkofer. Steger, G. Revach, R. J. G. van Sloun, and N. Shlezinger,  "SubspaceNet: Deep Learning-Aided Subspace Methods for DoA Estimation",  accepted to the IEEE Transactions on Vehicular Technology, 2024.

M. Malka, E. Farhan, H. Morgenstern, and N. Shlezinger, "Decentralized Low-Latency Collaborative Inference via Ensembles on the Edge", accepted to the IEEE Transactions on Wireless Communications, 2024. 

Y. Noah and N. Shlezinger, "Limited Communications Distributed Optimization via Deep Unfolded Distributed ADMM", accepted to the IEEE Transactions on Mobile Computing, 2024.

T. Raviv and N. Shlezinger, "Modular Hypernetworks for Scalable and Adaptive Deep MIMO Receivers", accepted to the IEEE Open Journal on Signal Processing,  2024.

October

• Once a year, the IEEE Signal Processing Society announces its 25 most downloaded articles and magazine papers. This year I am honored to have 4 different papers in this list. These papers are:

  • • "Integrated Sensing and Communications With Reconfigurable Intelligent Surfaces: From signal modeling to processing"

    • "Multiuser MIMO Wideband Joint Communications and Sensing System With Subcarrier Allocation"

    • "KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics" (second year in a row)

    • "Joint Transmit Beamforming for Multiuser MIMO Communications and MIMO Radar" (third year in a row)

• I have recently had the fortune to be teaming up with an awesome group of researchers for the task of fleshing up a tutorial on the various approaches for designing AI-aided Kalman filters. The outcome is now available as a preprint on Arxiv.

• The following journal papers were accepted for publication:

S. Truzman, G. Revach, N. Shlezinger, and I. Klein, "Outlier-Insensitive Kalman Filtering: Theory and Applications",  accepted to IEEE Sensors, 2024.

N. Lang, A. Cohen, and N. Shlezinger, "Stragglers-Aware Low-Latency Synchronous Federated Learning via Layer-Wise Model Updates",  accepted to the IEEE Transactions on Communications, 2024. 

• The following paper was accepted to NeurIPS 2024:

L. H. Cubillos, G. Revach, M. Mender, J. T. Costello, H. Temmar, A. Hite, D. A. K. Zutshi, D. M. Wallace, X. Ni, M. M. Kelberman, M. Willsey, R. Van Sloun, N. Shlezinger, P. G. Patil, A. Draelos, and C. Chestek, "Exploring the trade-off between deep-learning and explainable models for brain-machine interfaces", Advances in Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2024.

September

• Our study on learning of neuromorphic ADCs as a holistic task-based acquisition system is now available on Arxiv.

• The following journal paper was accepted for publication:

N. Nguyen, L. V. Nguyen, N. Shlezinger, Y. C. Eldar, A. L. Swindelhurst, and M. Juntti,  "Joint Communications and Sensing Hybrid Beamforming Design via Deep Unfolding",  accepted to the IEEE Journal on Selected Topics in Signal Processing, 2024.

August 2024

• Our new study on leaky wave antennas for wideband multi-user communications is available on Arxiv.

• We have a new paper on learned optimization for rapid and power-aware modular beamforming. It is available on Arxiv.

• Our new preprint proposing a new approach for combining deep learning with particle filters can be found on Arxiv.

• A new preprint on modular hypernetworks for deep receivers is available on Arxiv.

• The following journal papers were accepted for publication:

G. Fontanesi, A. Guerra, F. Guidi, J. Vasquez-Peralvo, N. Shlezinger, A. Zanella, E. Lagunas, S. Chatzinota, D. Dardari, and P. Djuric, "A Deep-NN Beamforming Approach for Dual Function Radar-Communication THz UAV", accepted to the IEEE Transactions on Vehicular Technology, 2024.

G. Revach, T. Locher, N. Shlezinger, R. J. G. van Sloun, and R. Vullings,  "HKF: Hierarchical Kalman Filtering with Online Learned Evolution Priors for Adaptive ECG Denoising",  accepted to the IEEE Transactions on Signal Processing, 2024.

July 2024

• The results for IEEE SPAWC 2024 are in. This year we will be presenting three papers from our group, in areas including deep learning for wireless receivers, tracking of dynamic systems, and wireless localization. 

• The following journal paper was accepted for publication:

I. Buchnik, G. Sagi, N. Leinwand,  Y. Loya,  N. Shlezinger, and T. Routtenberg, "GSP-KalmanNet: Tracking Graph Signals via Neural-Aided Kalman Filtering", accepted to the IEEE Transactions on Signal Processing, 2024.

June 2024

• Our recent work that uses deep unfolding to rapidly learn superposition codes in shared ad-hoc networks is available on Arxiv.

May 2024

• It is a great honor to be among the 10 recipients of the 2024 Krill prize, awarded annually by the Wolff foundations to leading Israeli scientists across multiple disciplines. 

• I am extremely honored to receive the 2024 IEEE Communications Society Fred W. Ellersick prize, an award granted annually recognizing a magazine article of notable contribution, for our article on dynamic metasurface antennas for massive MIMO, published in the IEEE Wireless Communications Magazine on April 2021.

April 2024

• The following journal papers were accepted for publication:

A. Milstein, H. Deng, G. Revach, H. Morgenstern, and N. Shlezinger, "Neural Augmented Kalman Filtering with Bollinger Bands for Pairs Trading", accepted to the IEEE Transactions on Signal Processing, 2024.

N. Shlezinger, M. Ma, O. Lavi, N. Nguyen, Y. C. Eldar, and M. Juntti, "AI-Empowered Hybrid MIMO Beamforming",  accepted to the IEEE Vehicular Technology Magazine, 2023.

March 2024

• Our recent paper which proposes a modular Bayesian deep learning approach for DNN-aided receivers is now available at Arxiv.

• We have a new preprint on straggler-aware fedetaed learning with provable convergence. You can find it at Arxiv.

February 2024

• The following journal papers were accepted for publication:

A. Rabault, L. Le Magoarou, J. Sol, G. C. Alexandropoulos, N. Shlezinger, H. V. Poor, and P. del Hougne, "On the Tacit Linearity Assumption in Common Cascaded Models of RIS-Parametrized Wireless Channels", accepted to the IEEE Transactions on Wireless Communications, 2024.

I. Morad, M. Ghelman, D. Ginzburg, A. Osovizky, and N. Shlezinger, "Model-Based Deep Learning Algorithm for Detection and Classification at High Event Rates",  accepted to the IEEE Transactions on Nuclear Science, 2024.

January 2024

• After 110 days away from home and office, I am finally back to my (pseudo) normal life.  While my TODO list has grown into a TODO book in my long absence, I consider myself to be fortunate. I am grateful to my colleagues and students who kept many of our projects active in this period, and looking forward to all the catching up. 

• We have a new paper on data-driven factor graphs for blind symbol detection up at Arxiv.

December 2023

• The results for ICASSP 2024 were published. Our group will be presenting 10 different works (one of which is a journal paper), spanning all aspects studied in the lab: model-based deep learning, signal acquisition, MIMO systems, etc. Moreover, we will be presenting a tutorial on flexible AI for wireless communications. Will be an interesting week...

• Our recent work presenting the potential of leaky waveguide antennas for wireless communications at THz bands is now available at Arxiv.

November 2023

• I usually try to post here updates on research-related activity on a weekly or bi-weekly basis. The last 8 weeks were an exception. It's not that nothing happened research-wise, but that too much non-research things happened. Both me and many of my lab members are deeply affected by the horrors that took place in October 7th and the war that has been raging since.  

• Despite all this, me and my lab have cool research related updates. Specifically, the following journal papers were accepted for publication:

G. Revach, X. Ni, N. Shlezinger, R. J. G. van Sloun, and Y. C. Eldar, "RTSNet: Learning to Smooth in Partially Known State-Space Models", accepted to the IEEE Transactions on Signal Processing, 2023.

T. Raviv, S. Park, O. Simeone, Y. C. Eldar, and N. Shlezinger, "Adaptive and Flexible Model-Based AI for Deep Receivers in Dynamic Channels",  accepted to the IEEE Wireless Communications, 2023.

G. C. Alexandropoulos, N. Shlezinger, I. Alamzadeh, M. F. Imani, H. Zhang, and Y. C. Eldar, "Hybrid Reconfigurable Intelligent Metasurfaces: Enabling Simultaneous Tunable Reflections and Sensing for 6G Wireless Communications", accepted to the IEEE Vehicular Technology Magazine, 2023.

• A new paper on hierarchical Kalman filtering for ECG denoising is now available on Arxiv.

• Our recent work that fuses graph signal processing, Kalman filtering, and deep learning for tracking of graph signals can be found on Arxiv.

October 2023

• Our recent paper on deep unfolded distributed optimization can be found on Arxiv.

September 2023

• Our recent paper on hybrid model-based/data-driven Kalman-based pairs trading can be found on Arxiv.

• The following journal papers were accepted for publication:

J. Merkofer, G. Revach, N. Shlezinger, T. Routtenberg, and R. J. G. van Sloun, "DA-MUSIC: Data-Driven DoA Estimation via Deep Augmented MUSIC Algorithm", accepted to the IEEE Transactions on Vehicular Technology, 2023.

N. Nguyen, M. Ma, O. Lavi, N. Shlezinger, Y. C. Eldar, A. L. Swindelhurst, and M. Juntti, "Deep Unfolding Hybrid Beamforming Designs for THz Massive MIMO Systems",  accepted to the IEEE Transactions on Signal Processing, 2023.

August 2023

• I am very proud to announce that our monograph on model-based deep learning has been published. I have worked quite extensively on fleshing up the main concepts of model-based deep learning in a manner which (I hope) is accessible, useful, and easy to follow. The monograph is available here, and has been published as

N. Shlezinger, and Y. C. Eldar, "Model-Based Deep Learning", In Foundations and Trends in Signal Processing, Now Publishers, 2023.

• Our recent work on compressed and private coding and aggregation for federated learning over massive networks is available on Arxiv.

• The following journal paper was accepted for publication:

N. Nguyen, N. Shlezinger, Y. C. Eldar, and M. Juntti, "Multiuser MIMO Wideband Joint Communications and Sensing System with Subcarrier Allocation",  accepted to the IEEE Transactions on Signal Processing, 2023.

July 2023

• Our paper "Joint Communications and Sensing Design for Multi-Carrier MIMO Systems" received the IEEE SSP 2023 best paper award!

• Our recent work on deep unfolding for joint communications and sensing is available on Arxiv.

• We now have a LinkedIn page for our lab! I highly recommend to follow it to keep track of the research and developments we are working on,

June 2023:

• Our recent paper on learning-aided subspace-based DoA estimation can be found on Arxiv.

• We have been working extensively on trying to frame our experience and understanding on model-based deep learning in an accessible tutorial-style monograph. Its first version is now availalbe in Arxiv, and it is accompanied with detailed examples in both math and code.

• We opened a GitHub repository for the algorithms developed in our lab. It is available here. We are still working on it, but it already includes the source code for some of our projects, and it will gradually grow to make the outcome of our research work reproducible and replicable. 

• The following jounral paper was accepted for publication:

O. Lavi and N. Shlezinger, "Learn to Rapidly and Robustly Optimize Hybrid Precoding", accepted to the IEEE Transactions on Communications, 2023.

May 2023:

• Our new tutorial on designing deep learning-aided receivers for dynamic channels is available on Arxiv.

• The paper “Federated Learning: A Signal Processing Perspective” has been identified as being one of the IEEE Signal Processing Society’s top 25 downloaded articles in 2022 for IEEE Signal Processing Magazine.

April 2023:

• Our recent work on data-aided Kalman-based tracking with high-dimensional observations can be found on Arxiv.

• ICASSP workshop results are in. Congratulations to my students Itay Buchnik and May Malka whose papers were accepted! Overall, I will be co-authoring 16 papers presented in ICASSP: 12 in the main track, 2 workshop papers, and 2 journal paper presentations.

• The following journal papers were accepted for publication:

E. Abakasanga, N. Shlezinger, and R. Dabora, "Deep-Learning-Aided Distributed Clock Synchronization for Wireless Networks", accepted to the IEEE Transactions on Vehicular Technology, 2023.

G. Choi, J. Park, N. Shlezinger, Y. C. Eldar, and N. Lee,  "Split-KalmanNet: A Robust Model-Based Deep Learning Approach for State Estimation",  accepted to the IEEE Transactions on Vehicular Technology, 2023.

N. Shlezinger and T. Routtenberg, "Discriminative and Generative Learning for Linear Estimation of Random Signals [Lecture Notes]",  accepted to the IEEE Signal Processing Magazine, 2023.

S. P. Chepuri, N. Shlezinger, F. Liu, G. C. Alexandropoulos, S. Buzzi, and Y. C. Eldar, "Integrated Sensing and Communications with Reconfigurable Intelligent Surfaces",  accepted to the IEEE Signal Processing Magazine, 2023.

March 2023:

• Our recent overview paper on AI for hybrid beamforming can be found on Arxiv.

• The following journal paper was accepted for publication:

T. Raviv and N. Shlezinger, "Data Augmentation for Deep Receivers",  accepted to the IEEE Transactions on Wireless Communications, 2023.

February 2023:

• ICASSP results are in. This year I am co-authoring 12 (!) accepted papers. Congratulations to my students Natalie Lang, Guy Revach, Solomon Goldgraber Casspi, Yoav Noah, Dor Shmuel, and Itay Buchnik whose papers were accepted!

• Our paper on the validity of the common cascaded model for smart programmable channels is available on Arxiv.

• The following journal papers were accepted for publication:

N. Shlezinger, J. Wang, Y. C. Eldar, and A. G. Dimakis,  "Model-Based Deep Learning",  accepted to the Proceedings of the IEEE, 2023. 

B. Salafian, E. Fishel, N. Shlezinger, S. Ribaupierre, and N. Farsad, "MICAL: Mutual Information-Based CNN-Aided Learned Factor Graphs for Seizure Detection from EEG Signals", accepted to the IEEE Access, 2023.

January 2023:

• Our recent work on unfolded robust MIMO beamforming can be found on Arxiv.

• Four journal papers were accepted for publication this month:

T. Raviv, S. Park, O. Simeone, Y. C. Eldar, and N. Shlezinger, "Online Meta-Learning For Hybrid Model-Based Deep Receivers", accepted to the IEEE Transactions on Wireless Communications, 2023.

N. Lang, E. Sofer, T. Shaked, and N. Shlezinger, "Joint Privacy Enhancement and Quantization in Federated Learning",  accepted to the IEEE Transactions on Signal Processing, 2023.

B. Wolff, T. Gafni, G. Revach, N. Shlezinger, and K. Cohen, "Anomaly Search over Composite Hypotheses in Hierarchical Statistical Models",  accepted to the IEEE Transactions on Signal Processing, 2023.

H. Zhang, A. Shultzman, N. Shlezinger, G. C. Alexandropoulos, M. F. Imani, and Y. C. Eldar, "Channel Estimation with Hybrid Reconfigurable Intelligent Metasurfaces", accepted to the IEEE Transactions on Communications, 2023.

December 2022:

• Our work on power-efficient robust hybrid MIMO design is available on Arxiv.

• The following journal paper was accepted for publication:

H. Zhang,  N. Shlezinger, F. Guidi, D. Dardari, and Y. C. Eldar, "6G Wireless Communications: From Far-field Beam Steering to Near-field Beam Focusing", accepted to the IEEE Communications Magazine, 2022.

November 2022:

• Our tutorial paper on reconfigurable intelligent surfaces for integrated sensing and communications can be found on Arxiv.

• The following journal papers were accepted for publication:

N. Shlezinger and I. V. Bajic, "Collaborative Inference for AI-Empowered IoT Devices", accepted to the IEEE Internet-of-Things Magazine, 2022.

N. Shlezinger, A. Amar, B. Luijten, R. J. G. van Sloun, and Y. C. Eldar, "Deep Task-Based Analog-to-Digital Conversion", accepted to the IEEE Transactions on Signal Processing, 2022.

October 2022:

• The following journal paper was accepted for publication:

N. Shlezinger, Y. C. Eldar, and S. P. Boyd, "Model-Based Deep Learning: On the Intersection of Deep Learning and Optimization", accepted to IEEE Access, 2022.  

September 2022:

• Our paper on data augmentation of deep receivers is available on Arxiv.

• Congratulations to Itay Buchnik for being awarded the best student presentation in the 2022 IEEE-SPS/EURASIP Summer School!

August 2022:

• Our paper on anomaly detection with hierarchical data can be found on Arxiv.

• Our work on joint quantization and privacy enhancement is now available on Arxiv.

• The following journal papers were accepted for publication:

R. Faqiri, C. Saigre-Tardif, G. C. Alexandropoulos, N. Shlezinger, M. F. Imani, and P. del Hougne, "PhysFad: Physics-Based End-to-End Channel Modeling of RIS-Parametrized Environments with Adjustable Fading",  accepted to the IEEE Transactions on Wireless Communications, 2022.

P. Li, N. Shlezinger, H. Zhang, B. Wang, and Y. C. Eldar, "Compression of Graph Signals using Task-Based Sampling and Quantization", accepted to the IEEE Transactions on Signal Processing, 2022.

July 2022:

• Our overview on AI-aided collaborative inference is available on Arxiv.

• The following journal paper was accepted for publication:

T. V. Loung, N. Shlezinger, C. Xu, T. M. Hoang, Y. C. Eldar, and L. Hanzo,  "Deep Learning Based Successive Interference Cancellation for the Non-Orthogonal Downlink",  accepted to the IEEE Transactions on Vehicular Technology, 2022. 

June 2022:

• Our work on collaborative inference via ensembles on the edge is available on Arxiv.

• Our paper on channel estimation with hybrid RISs can be found on Arxiv.

May 2022:

• Our paper "Deep Task-Based Quantization" published in Entropy last year was selected for the Editor's Choice Articles (see LinkedIn)

• Two papers from my group were accepted to EUSIPCO 2022. 

• Our recent tutorial article on model-based deep learning is available on Arxiv.

• The three papers we submitted to SPAWC were accepted. Congratulations to the students Ortal Agiv and Tomer Raviv for having their papers accepted.

April 2022:

• ISIT results are in. This year I am co-authoring three accepted papers, and will present a tutorial. Congratulations to the PhD students Natalie Lang and Guy Revach for having their papers accepted.

• Our work on online meta-learning for deep receivers can be found on Arxiv.

• Thanks everyone in the lab for teaming up for volunteering for food packaging for Passover with the Be'er Sova initiative. Was a great experience.

March 2022:

• Our work on the role and potential of near-field communications in 6G networks is available on Arxiv. 

• The paper “Joint Transmit Beamforming for Multiuser MIMO Communications and MIMO Radar” has been identified as being one of the IEEE Signal Processing Society’s top 25 downloaded articles in 2021 for IEEE Transactions on Signal Processing. 

• The following journal papers were accepted for publications

 G. Revach, N. Shlezinger, X. Ni,  A. L. Escoriza, R. J. G. van Sloun, and Y. C. Eldar, "KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics",  accepted to the IEEE Transactions on Signal Processing, 2022.

H. Zhang, N. Shlezinger, F. Guidi, D. Dardari, M. F. Imani, and, Y. C. Eldar, "Beam Focusing for Near-Field Multi-User MIMO Communications",  accepted to the IEEE Transactions on Wireless Communications, 2022. 

February 2022:

• Our work on deep learning for task-based analog-to-digital conversion design is now up on Arxiv.

• A new preprint describing a channel model for RIS-aided communication in fading environments is available on Arxiv.

January 2022:

• ICASSP results are in. This year I will be co-authoring nine papers, organizing a special session, and presenting a tutorial. Much thanks to the great work of my collaborators and students, and specifically to the PhD students Guy Revach (3 papers), Eyal Fishel (2 papers), and Tomer Raviv (1 paper).

• The following magazine article was accepted for publication:

H. Zhang, N. Shlezinger, F. Guidi, D. Dardari, M. F. Imani, and, Y. C. Eldar, "Near-field Wireless Power Transfer for 6G Internet-of-Everything Mobile Networks: Opportunities and Challenges",  Accepted to the IEEE Communications Magazine, 2022. 

December 2021:

• The following journal paper was accepted for publication:

N. Shlezinger, N. Farsad, Y. C. Eldar, and A. J. Goldsmith, "Learned Factor Graphs for Inference from Stationary Time Sequences", Accepted to the IEEE Transactions on Signal Processing, 2021.  

October 2021:

• Our work on hybrid metasurfaces is discussed in a dedicated post on the 6G World portal.

• Our recent work on graph signal compression via joint sampling and quantization can be found on Arxiv.

• Our work on deep learning aided Kalman smoothing is now available on Arxiv.

• The following journal papers were accepted for publication:

I. Alamzadeh, G. C. Alexandropoulos, N. Shlezinger, and M. F. Imani, "A Reconfigurable Intelligent Surface with Integrated Sensing Capability", Accepted to Nature Scientific Reports, 2021.

T. Gafni, N. Shlezinger, K. Cohen, Y. C. Eldar, and H. V. Poor,  "Federated Learning: A Signal Processing Perspective",  Accepted to the IEEE Signal Processing Magazine, 2021. 

September 2021:

• Three journal papers were accepted for publication this month:

F. Xi, N. Shlezinger, and Y. C. Eldar, "BiLiMO: Bit-Limited MIMO Radar via Task-Based Quantization", Accepted to the IEEE Transactions on Signal Processing, 2021.

S. Khobahi, N. Shlezinger, M. Soltanalian and Y. C. Eldar, "LoRD-Net: Low Resolution Detection Network for Deep Low-Resolution Receivers", Accepted to the IEEE Transactions on Signal Processing, 2021.

D. Ma, N. Shlezinger, T. Huang, Y. Liu, and Y. C. Eldar,  "FRaC: FMCW-Based Joint Radar-Communications System via Index Modulation", Accepted to the IEEE Journal on Selected Topics in Signal Processing, 2021.

August 2021:

• Our paper on near-field wireless power transfer for 6G IoE devices is available on Arxiv. 

July 2021:

• Our recent paper proposing KalmanNet, which is a data-driven implementation of the celebrated Kalman filter, is now available on Arxiv.

• The following journal paper was accepted for publication:

P. Neuhaus, N. Shlezinger, M. Dorpinghaus, Y. C. Eldar, and G. Fettweis,  "Task-Based Analog-to-Digital Converters",  Accepted to the IEEE Transactions on Signal Processing, 2021.

June 2021:

• The following journal paper was accepted for publication:

T. Sery, N. Shlezinger, K. Cohen, and Y. C. Eldar,  "Convergent Over-the-Air Federated Learning from Heterogeneous Data", Accepted to the IEEE Transactions on Signal Processing, 2021.

• Our paper "Model-Based Deep Learning: Key Approaches and Design Considerations" was awarded the Audience Choice Paper Award in the IEEE Data Science and Learning Workshop (DSLW) 2021.

May 2021:

• Our new paper on near-field beam focusing in MIMO communications is available on Arxiv.

• The following journal paper was accepted for publication:

A. Cohen, N. Shlezinger, S, Salamatian, Y. C. Eldar, and M. Medard,  "Serial Quantization for Sparse Time Sequences", Accepted to the IEEE Transactions on Signal Processing, 2021.

• Three conference papers which I am co-authoring have been accepted: one on task-based analog-to-digital conversion was accepted to EUSIPCO, and two on the interface of machine learning and wireless communications will be presented in SSP on August.

April 2021:

• The following magazine article was accepted for publication:

G. C. Alexandropoulos, N. Shlezinger, and P. del Hougne, "Reconfigurable Intelligent Surfaces for Rich Scattering Wireless Communications: Recent Experiments, Challenges, and Opportunities", Accepted to the IEEE Communications Magazine,  2021.

• Our recent paper on hybrid reconfigurable intelligent surfaces for wireless communications can now be found on Arxiv.

• Our tutorial-style overview of signal processing and communication methods for the emerging federated learning paradigm is now available on Arxiv.

March 2021:

• Our recent work on combining online meta-learning with data-driven Viterbi detection is available on Arxiv.

• I am authoring two accepted paper in this year's ICC. Both are on the interface of wireless communications and deep learning.

• There is a good deal of research on reflective metasurfaces for wireless communication, and the common assumption is that communication is carried out in (quasi)  free space. In our recent work, now available on Arxiv, we show how such metasurfaces can be utilized for rich scattering channels (e.g., dense indoor setups), and what are the gains one can hope for.

February 2021:

• The following journal paper was accepted for publication:

M. Chen, N. Shlezinger, H. V. Poor, Y. C. Eldar,  and S. Cui, "Communication-Efficient Federated Learning", Accepted to the Proceedings of the National Academy of Science,  2021.

• Our recent work on unfolded low-resolution receivers is now available on Arxiv.

January 2021:

• ICASSP 2021 results are in. This year I am authoring seven accepted papers, and presenting one tutorial. Just like last year's ICASSP...

• The following journal papers were accepted for publication:

N. Shlezinger and Y. C. Eldar, "Deep Task-Based Quantization", Accepted to Entropy, 2021. 

D. Ma, N. Shlezinger, T. Huang, Y. Shavit, M. Namer, Y. Liu, and Y. C. Eldar,  "Spatial Modulation for Joint Radar-Communications Systems: Design, Analysis, and Hardware Prototype", Accepted to the IEEE Transactions on Vehicular Technology, 2021. 

December 2020:

• Our overview paper on model-based deep learning is available on Arxiv.

• The following journal papers were accepted for publication:

N. Shlezinger, M. Chen, Y. C. Eldar, H. V. Poor, and S. Cui, "UVeQFed: Universal Vector Quantization for Federated Learning", Accepted to the IEEE Transactions on Signal Processing,  2020.

N.  Shlezinger,  G.  C.  Alexandropoulos,  M.  F.  Imani,  Y.  C.  Eldar,  and  D.  R.  Smith, "Dynamic Metasurface Antennas for 6G Extreme Massive MIMO Communications", Accepted to the IEEE Wireless Communications Magazine, 2020. 

November 2020:

• The following journal paper was accepted for publication:

H. Wang, N. Shlezinger, Y. C. Eldar, S. Jin, M. F. Imani, I. Yoo, and D. R. Smith, "Dynamic Metasurface Antennas for MIMO-OFDM Receivers with Bit-Limited ADCs", Accepted to the IEEE Transactions on Communications, 2020.

October 2020:

• I was awarded the Feinberg Graduate School prize for outstanding achievements in postdoctoral research.

• Our new paper on bit-limited MIMO radar receivers is up on Arxiv. 

• The following journal paper was accepted for publication:

N. Shlezinger, R. Fu, and Y. C. Eldar, "DeepSIC: Deep Soft Interference Cancellation for Multiuser MIMO Detection", Accepted to the IEEE Transactions on Wireless Communications, 2020. 

September 2020:

• Our paper on task-based analog-to-digital conversion can be found on Arxiv.

• Our work on convergent over-the-federated learning is now available on Arxiv.

• The following journal papers were accepted for publication:

T. Huang, N. Shlezinger, X. Xu, D. Ma, Y. Liu, and Y. C. Eldar, "Multi-Carrier Agile Phased Array Radar", Accepted to the IEEE Transactions on Signal Processing, 2020.

N. Shlezinger  and Y. C. Eldar,  "Task-Based Quantization with Application to MIMO Receivers", Accepted to Communications in Information and Systems, Special issue in honor of Thomas Kailath's 85th Birthday, invited paper, 2020.

N. Farsad, N. Shlezinger, A. J. Goldsmith,  and Y. C. Eldar,  "Data-Driven Symbol Detection via Model-Based Machine Learning", Accepted to Communications in Information and Systems, Special issue in honor of Thomas Kailath's 85th Birthday, invited paper,  2020. 

August 2020:

• Our paper on convergent over-the-air federated learning was accepted to GlobeCom.

July 2020:

• Our work on energy harvesting analog-to-digital converters can be found on Arxiv.

June 2020:

• We have posted on Arxiv our recent paper on dynamic metasurface antennas for wireless communications.

• Our paper on universal vector quantization for federated learning is now available on Arxiv.

• We have uploaded our recent work on inference from stationary time sequences using learned factor graphs to Arxiv. 

• The following journal paper was accepted for publication:

X. Liu, T. Huang, N. Shlezinger, Y. Liu, J. Zhou, and Y. C. Eldar, "Joint Transmit Beamforming for Multiuser MIMO Communications and Radar", Accepted to the IEEE Transactions on Signal Processing, 2020.

May 2020:

• ICASSP takes place as a virtual conference. A video of our tutorial on machine learning and wireless communications (with Yonina Eldar and Vince Poor) is available on the ICASSP virtual platform in this link, and the slides are available here.  

• The following journal paper was accepted for publication:

T. Huang, N. Shlezinger, X. Xu, Y. Liu, and Y. C. Eldar, "MAJoRCom: A Dual-Function Radar Communication System Using Index Modulation", Accepted to the IEEE Transactions on Signal Processing, 2020.

April 2020:

• I will be joining the School of Electrical and Computer Engineering in Ben-Gurion University as an assistant professor starting October 2020.

March 2020:

• Two papers accepted to ISIT, both on the interface of machine learning and information theory.

• The following journal paper was accepted for publication:

E. Abakasanga, N. Shlezinger, and R. Dabora, "On the Rate-Distortion Function of Sampled Cyclosationary  Gaussian Processes", Accepted to Entropy, 2020. 

• Our work on the rate-distortion of sampled cyclostationary sources can now be found in Arxiv.

February 2020:

• The following journal papers were accepted for publication:

T. Gong, N. Shlezinger, S. Stein-Ioushua, M. Namer, Z. Yang, and Y. C. Eldar, "RF Chain Reduction for MIMO Systems: A Hardware Prototype", Accepted to the IEEE Systems Journal, 2020.

D. Ma, N. Shlezinger, T. Huang, Y. Liu, and Y. C. Eldar, "Joint Radar-Communications Strategies for Autonomous Vehicles", Accepted to the IEEE Signal Processing Magazine, 2020.

• A paper detailing our approach to model-based machine learning for symbol detection was posted to Arxiv.

• My tutorial paper on task-based quantization is now available on Arxiv.

• My paper on DeepSIC, which is a receiver architecture that learns to cancel interference, is now up on Arxiv.

• Check out our recent work on data-driven factor graphs for symbol detection on Arxiv.

• Our work on joint beamforming for dual function radar communication systems is available on Arxiv.

January 2020:

• The seven papers I submitted to ICASSP 2020 were all accepted. Will also be giving a tutorial (with Yonina Eldar and Vince Poor) and present some of the demos we have been working on. It's going to be a busy week...

• The following journal paper was accepted for publication:

N. Shlezinger, N. Farsad, Y. C. Eldar, and A. J. Goldsmith, "ViterbiNet: Symbol Detection Using a Deep Learning Based Viterbi Algorithm", Accepted to the IEEE Transactions on Wireless Communications, 2020.

•  Our recently submitted paper on dynamic metasurface antennas for bit-limited receivers is now available on Arxiv.