Prof. Mérouane Debbah Receives Double Accolade: Ranks No.1 in France, and 180th globally among Top 1,000 Scientists, and among the 2,000 most influential scholars for Internet of Things for 2022.
Prof. Mérouane Debbah, Chief Researcher at the AI Cross-Center Unit and DSRC, has been ranked No. 1 in France and 180th globally in Electronics and Electrical Engineering by Research.com. He has an H-index of 98 and over 47000 citations. Debbah was also recognized as a 2022 AI 2000 Most Influential Scholar in Internet of Things for contributions between 2012 and 2021. Why it matters: This recognition highlights the growing AI research talent within the GCC region, particularly in areas related to communication technologies and IoT.
MBZUAI Adjunct Professor Mérouane Debbah was named a Highly Cited Researcher by Clarivate, placing him in the top 1% of researchers globally. Debbah, who joined MBZUAI's machine learning department in 2021, also serves as chief researcher at the Technology Innovation Institute (TII) in Abu Dhabi. His research focuses on multi-agent reinforcement learning, distributed AI, and applying AI to improve telecommunications, including reducing dead spots and improving energy efficiency. Why it matters: This recognition highlights the UAE's growing prominence in AI research, particularly in leveraging AI for advancements in telecommunications infrastructure and multi-agent systems.
The Technology Innovation Institute (TII) congratulated Prof. Merouane Debbah, Chief Researcher of AI & Telecoms Systems, for being included in Clarivate’s 2021 Highly Cited Researchers List. This list recognizes Prof. Debbah as being in the top 1% of researchers worldwide. TII expressed pride in this global recognition of Prof. Debbah's work. Why it matters: This highlights the UAE's growing prominence in attracting and supporting top AI researchers, enhancing its reputation as an innovation hub.
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.
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.