Rate My Professor Noa Zilberman

Her research focuses on the integration of micro-level architectures and macro-level large-scale networked systems, spanning computer architecture, programmable hardware, networking, and data science, with an emphasis on measurements across disciplines. Current interests include sustainable and resilient computing infrastructure, systems for AI, networked-systems architectures, rack-scale computing, in-network computing and machine learning, memory architectures and performance, and carbon-aware networking. She is a Senior Member of IEEE and ACM, Turing Fellow (2024-2025), and IEEE ComSoc Distinguished Lecturer (2023-2024). As a recognized expert, she advises government and funding agencies on computing infrastructure. Key publications include "Planter: rapid prototyping of in-network machine learning inference" (ACM SIGCOMM Computer Communication Reviews, 2024; Best of CCR at SIGCOMM), "In-Network Machine Learning Using Programmable Network Devices: A Survey" (IEEE Communications Surveys & Tutorials, 2023), "DINC: toward distributed in-network computing" (ACM CoNEXT, 2023), "Toward Carbon-Aware Networking" (ACM SIGEnergy Energy Informatics Review, 2023), and "Exploring the Benefits of Carbon-Aware Routing" (ACM CoNEXT, 2023; IRTF Applied Networking Research Prize and STEM for Britain 2024 Dyson Sustainability Award). Her contributions have advanced in-network machine learning for cybersecurity, finance, and smart environments, alongside efforts to enhance AI sustainability.