Kristoffer – Rust, IPFS, Ethereum

The project focused on building a compiler that translates programs written in a smart contract–oriented programming language into WebAssembly. The solution aimed to enable efficient execution, portability, and interoperability of smart contracts across different runtime environments. It involved parsing and semantic analysis, intermediate representation design, and generation of optimized WebAssembly output, with an emphasis on correctness, determinism, and security required for blockchain-based execution environments.

• Modularized and refactored the initial compiler draft, improving code structure, readability, and long-term maintainability;
• Took ownership of ongoing maintenance, addressing bugs, and stabilizing core compilation workflows;
• Designed and implemented test coverage to validate parsing, semantic analysis, and WebAssembly code generation;
• Improved compiler reliability by introducing automated testing and regression safeguards;
• Collaborated on refining compilation stages to ensure correctness, determinism, and compatibility with blockchain execution constraints.

The project developed a WebAssembly-based execution environment for smart contracts, enabling secure, deterministic, and high-performance execution of decentralized applications. It handled contract deployment, execution, and state management, with isolation, resource metering, and concurrency support. The platform ensured predictable performance, security, and seamless integration with blockchain consensus mechanisms, allowing developers to deploy WebAssembly smart contracts efficiently and reliably.

• Developed a WebAssembly execution environment for smart contracts, primarily targeting Rust while supporting any language that compiles to WebAssembly;
• Optimized binary output to achieve extremely small sizes, reducing typical smart contract binaries from ~100 KB to under 1 KB, significantly improving performance in consensus evaluation;
• Focused on high-performance execution to meet the demands of Ethereum-style consensus, where every node evaluates every program;
• Led a team of two engineers, overseeing development, code quality, and project delivery;
• Maintained and ensured the continued operational use of the platform in production environments.

Rust-based Ethereum client enabling secure and efficient interaction with the blockchain. The client handled transaction validation, block propagation, consensus, and network peer management, leveraging Rust for performance, memory safety, and concurrency. It supported full node operations, smart contract execution, and seamless synchronization with the Ethereum network.

• Joined as an early team member to contribute to the development of the first Rust-based Ethereum client;
• Implemented core blockchain functionality, including transaction validation, block propagation, and consensus mechanisms;
• Developed network peer management features to ensure reliable node communication and synchronization;
• Optimized the client for performance, memory safety, and concurrency using Rust;
• Supported full node operations and smart contract execution, enabling developers to interact with the Ethereum network effectively.

The project involved building a distributed system for performing high-performance GeoIP lookups. It enabled efficient querying of geolocation information across a decentralized network, ensuring scalability, low latency, and reliability. The system was designed to handle large volumes of requests, support fault tolerance, and provide accurate geolocation data for applications requiring geographic context in distributed environments.

• Designed and implemented a distributed B-Tree lookup structure for geolocation data over a peer-to-peer network;
• Replaced reliance on third-party servers by enabling clients to perform location lookups directly over the decentralized network;
• Optimized the system so each client fetched only relevant subsets of data, reducing bandwidth usage and improving efficiency;
• Leveraged caching mechanisms within the peer-to-peer network to ensure fast and repeated access to lookup data;
• Enhanced scalability and resilience of geolocation queries in a fully decentralized environment.