Simon Knight, PhD

I specialize in the architecture of intelligent systems and network automation. My work bridges the gap between high-level intent and low-level execution through formal modeling, deterministic simulation, and multi-agent coordination.

Core Expertise

My work centers on building the right abstractions and transformations for complex systems:

• Systems Design: Emphasizing systematic planning, type-safe interfaces, and comprehensive test coverage as first-class citizens. Designing systems that transform high-level intent into executable implementations through well-defined layers of abstraction.
• Network Automation: Developing high-performance Rust engines for topology modeling, protocol simulation, and configuration generation. Building tools that enable declarative network design with multi-vendor support.
• Advanced Data Visualization and Analytics: Creating information-dense visualizations that reduce complexity and reveal structure. Processing large-scale geospatial and network datasets with high-performance analytics pipelines.
• Signal Processing: Building modular ecosystems for real-time RF spectrum monitoring and analysis through high-performance SDR pipelines and spatial audio processing.
• Agent Architectures: Designing secure, message-bus-driven multi-agent systems with strong isolation boundaries and deterministic behavior.

I focus on building tools that solve the “information noise” problem—transforming complex, raw data into clear, actionable visualizations and configurations through well-designed abstractions.

Research & Background

I completed my PhD at the University of South Australia in 2017. My thesis, Abstractions and Transformations for Automated Data Network Configuration, pioneered a compiler-based approach to transform high-level network specifications into multi-platform device configurations.

This research led to the creation of AutoNetkit, an open-source tool integrated into Cisco’s VIRL platform for automated network lab provisioning. I continue to evolve these abstractions in my current projects.

Active Projects

I am currently developing a suite of interconnected tools:

• NetVis: A high-performance visualization engine for complex network topologies.
• ank-pydantic: Type-safe topology modeling backed by a Rust graph core.
• Secure Multi-Agent Assistant: A containerized agent framework for secure automation.

View all projects

Domain Focus

I build systems that transform high-level intent into deterministic execution through well-defined layers of abstraction.

• Network Automation: High-performance Rust engines for topology modeling, protocol simulation, and multi-vendor configuration generation.
• Signal Processing: Real-time RF spectrum monitoring and biometric signal analysis using modular, high-throughput acquisition pipelines.
• Agent Architectures: Secure, message-bus-driven multi-agent systems focusing on strong isolation, capability-based security, and deterministic coordination.
• Data & Simulation: High-performance analytics engines (Rust/Polars) for massive geospatial datasets and time-series pattern discovery.

Research & Background

I completed my PhD at the University of South Australia in 2017. My thesis, Abstractions and Transformations for Automated Data Network Configuration, pioneered a compiler-based approach to transform high-level network specifications into multi-platform device configurations.

This research led to AutoNetkit, an open-source tool integrated into Cisco’s VIRL platform for automated network lab provisioning. My current work evolves these abstractions into high-performance, type-safe implementations.