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Professor Pascal Saikaly named International Honorary Member by AAEES

KAUST · · Notable

Summary

Professor Pascal Saikaly of KAUST has been named the 2024 International Honorary Member of the American Academy of Environmental Engineers and Scientists (AAEES). Saikaly was selected for his contributions to the advancement of environmental protection, specifically his work in developing sustainable biotechnologies for wastewater reclamation and reuse. He developed a patented technology for a decentralized wastewater recycling plant demonstrated at full scale in Saudi Arabia. Why it matters: This award recognizes important work in sustainable wastewater treatment, an area of critical importance for water-scarce regions like Saudi Arabia.

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KAUST ·

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Addressing the world's water challenge: KAUST team develops novel wastewater treatment and reuse technology

KAUST ·

KAUST researchers led by Pascal Saikaly are developing microbial electrochemical technologies (METs) for wastewater treatment and energy recovery. The team combines METs with membrane filtration, creating a hybrid air-biocathode microbial fuel cell-membrane bioreactor (MFC-MBR) for simultaneous wastewater treatment and ultrafiltration. This system uses an electrically conductive ultrafiltration membrane as a biocathode for electricity generation and passive oxygen transfer. Why it matters: This innovation offers a sustainable approach to water reclamation by reducing energy consumption and producing reusable water, which addresses critical water scarcity challenges in the region and globally.

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

TII ·

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.