Biography
Prof Noa Zilberman leads the Computing Infrastructure Group at the Department of Engineering Science.
Her research focuses on the integration of micro-level architectures and macro level, large scale networked-systems. Zilberman's research interests range from computer architecture, programmable hardware and networking to data science, with a specific interest in the combination of multiple disciplines (and a touch of measurements). Current research interests include sustainable computing infrastructure, data systems, networked-systems architectures, in-network computing and in-network machine learning, performance measurements, and others.
Before joining Oxford, Prof Zilberman was a Fellow and an Affiliated Lecturer at the University of Cambridge' Department of Computer Science and Technology. Prof Zilberman has over 15 years of industrial experience. In her last role before moving to academia, she was a Senior Principal chip architect in Broadcom's Network Switching group.
Most Recent Publications
E-commerce bot traffic: in-network impact, detection, and mitigation
E-commerce bot traffic: in-network impact, detection, and mitigation
Iisy: hybrid in-network classification using programmable switches
Iisy: hybrid in-network classification using programmable switches
In-network machine learning using programmable network devices: a survey
In-network machine learning using programmable network devices: a survey
In-Network Machine Learning Using Programmable Network Devices: A Survey
In-Network Machine Learning Using Programmable Network Devices: A Survey
Exploring the benefits of carbon-aware routing
Exploring the benefits of carbon-aware routing
Research Interests
- Open source networking and computing research
- Sustainable computing
- Programmable platforms
- High performance networked systems
- Network switching architectures
- Computing architectures
- In-network computing
- Queuing and buffering
- Memory management
- Performance analysis
- High speed interfaces
Research Group
Most Recent Publications
E-commerce bot traffic: in-network impact, detection, and mitigation
E-commerce bot traffic: in-network impact, detection, and mitigation
Iisy: hybrid in-network classification using programmable switches
Iisy: hybrid in-network classification using programmable switches
In-network machine learning using programmable network devices: a survey
In-network machine learning using programmable network devices: a survey
In-Network Machine Learning Using Programmable Network Devices: A Survey
In-Network Machine Learning Using Programmable Network Devices: A Survey
Exploring the benefits of carbon-aware routing
Exploring the benefits of carbon-aware routing
DPhil Opportunities
I am always looking for outstanding graduate students to join the team, particularly those with an interest in programmable hardware, networking, systems and computer architecture. I would encourage potential students to contact me by email before applying.
Research Group
Most Recent Publications
E-commerce bot traffic: in-network impact, detection, and mitigation
E-commerce bot traffic: in-network impact, detection, and mitigation
Iisy: hybrid in-network classification using programmable switches
Iisy: hybrid in-network classification using programmable switches
In-network machine learning using programmable network devices: a survey
In-network machine learning using programmable network devices: a survey
In-Network Machine Learning Using Programmable Network Devices: A Survey
In-Network Machine Learning Using Programmable Network Devices: A Survey
Exploring the benefits of carbon-aware routing
Exploring the benefits of carbon-aware routing