Researchers from the AI and Digital Science Research Center (AIDRC) won the Best Paper Award at the 2022 IEEE Global Communications Conference (GLOBECOM) for their paper "RSMA for Dual-Polarized Massive MIMO Networks: A SIC-Free Approach". The paper introduces a dual-polarized RSMA technique for downlink massive MIMO networks, using the polarization domain. Their approach relaxes the computational burden of successive interference cancellation and delivers high data rates. Why it matters: This award recognizes impactful research from the UAE on optimizing wireless communication using AI, which can contribute to advancements in 5G and beyond.
Professor Mérouane Debbah, Chief Researcher at AIDRC, and his co-authors received the 2022 IEEE TAOS TC Best GCSN Paper Award for their work on federated quantized neural networks. The paper, presented at IEEE ICC 2022, explores the tradeoff between energy, precision, and accuracy in these networks. The research proposes an optimal quantization level to minimize energy consumption during training, making it less prohibitive for mobile devices. Why it matters: The award recognizes work that reduces the carbon footprint of large-scale AI systems, a key challenge for sustainable AI deployment in the region and globally.
AIDRC researchers co-authored an accepted IEEE Vehicular Technology Magazine article on time reversal for 6G wireless communications. The article presents experimental results on the spatiotemporal focusing capability of time reversal across carrier frequencies. It examines requirements for efficient time reversal operation and synergies with technologies like reconfigurable intelligent surfaces. Why it matters: The research explores advancements in 6G wireless communication, with potential implications for coverage extension, sensing, and localization capabilities in the region.
MBZUAI's Prof. Mérouane Debbah will receive two awards at the 2022 IEEE ICC in Seoul. One paper analyzes reconfigurable intelligent surfaces (RISs) for 6G, highlighting spectral efficiency gains. The other paper explores energy-efficient distributed AI algorithms using quantized neural networks. Why it matters: This recognition highlights MBZUAI's contributions to cutting-edge research in wireless communications and sustainable AI, positioning the institute as a leader in these fields.
A research paper co-authored by Dr. Maxim Panov and Kirill Fedyanin from the AI and Digital Science Research Center (AIDRC) has been accepted for publication at NeurIPS 2022. The paper, titled “Nonparametric Uncertainty Quantification for Single Deterministic Neural Network”, proposes a fast and scalable method for uncertainty quantification in ML models. The method disentangles aleatoric and epistemic uncertainties and was validated on text classification and image datasets including MNIST and ImageNet. Why it matters: This demonstrates the growing AI research capabilities and contributions from the UAE to the global AI community, particularly in fundamental machine learning research.