Professor Mérouane Debbah, co-authors receive 2022 IEEE TAOS TC Best GCSN Paper Award

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Congratulations to Prof. Mérouane Debbah, Chief Researcher, AI and Digital Science Research Center (AIDRC), and his co-authors Mohammad Mozaffari, Senior Researcher, Ericsson USA, Walid Saad and Minsu Kim, Professor and graduate research assistant respectively, at the Electrical and Computer Engineering Department, Virginia Tech!

Their research paper, titled "On the Tradeoff between Energy, Precision, and Accuracy in Federated Quantized Neural Networks" presented at IEEE ICC 2022 Green Communications Systems and Networks (GCSN) symposium, was awarded the 2022 IEEE TAOS TC Best GCSN Paper Award. The paper was selected by the IEEE Communication Society Transmission, Access, and Optical System (TAOS) Technical Committee (TC) among other papers presented at ICC 2022 and Globecom 2022 under the Green Communications Systems and Networks section in Seoul, South Korea.

The team was recognized for their pioneering work on using quantization to reduce the energy consumption in federated learning and proposing the optimal quantization level to minimize the total energy consumption during training. This makes the training process less prohibitive for most mobile devices and reduces the carbon footprint required to run large-scale AI systems.

We are extremely proud of the success and contributions of Prof. Debbah and his outstanding team! Here’s to many more industry accolades in the coming years!