Summary
Tu Hoang is a postdoctoral researcher and engineer with 11 years of experience building privacy-preserving distributed systems that bridge blockchain, zero-knowledge cryptography, and federated learning. Based in Hamburg, he has designed and implemented ZK-based decentralized identity, oracle, and federated/unlearning protocols that reduce on-chain costs (e.g., zkRollups with ~29.8% cost improvement vs Chainlink) and make ML workflows verifiable across heterogeneous clients. He combines practical engineering (Rust, TypeScript, Solidity, Go, Python) with academic rigor from a PhD in Computer Science, collaborating with industry partners like IOTA Foundation and Pantos to produce deployable systems on Ethereum and Hyperledger. His work uniquely fuses knowledge distillation, multimodal/private ML, and ZK proofs to enable verifiable training, aggregation, and unlearning, while also applying homomorphic and MPC techniques for privacy-aware analytics. Beyond research, he has shipped prototypes and smart-contract simulations, and has a background teaching databases and security, which informs his emphasis on auditable, deployable designs.
11 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Università degli Studi dell'Insubria
Master’s Degree, Master’s Degree at VNUHCM - University of Science
English, Vietnamese