Decentralized AI Systems | Blockchain Infrastructure | Multi-Chain Solutions | BTC vanity generation
I am a research and developer with 5+ years of experience with building decentralized systems specializing in Go and Rust languages. I have deep expertise in the Ethereum and Cosmos SDK ecosystems, smart contracts (EVM/WASM), systems programming, performance optimization, and high-throughput distributed systems.
I am also a specialized expert in Elliptic Curve Cryptography (ECC), with over ten years of focused research and engineering in performance optimization for elliptic curve computations. My work centers on minimizing execution latency and computational cost in large-scale cryptographic operations, especially scalar multiplication and finite field arithmetic over secp256k1 and related curves.
A major achievement in this area is the design and implementation of an ultra–high-performance Bitcoin vanity address generation system, engineered for massively parallel elliptic curve computations and large-scale search for pattern-constrained public addresses.
I am currently expanding into Decentralized AI system development, combining my blockchain infrastructure and cryptographic optimization background with cutting-edge AI/ML technologies to build the next generation of decentralized intelligent systems.
| Project | Description | Tech Stack |
|---|---|---|
| Echo Network | Contributed core staking module and i2p proxy to Echo Network L1 blockchain with zk-SNARKs and Mimblewimble protocol integration. |   |
| BTC vanity address generator | Developed algorithms to speeding up the cost and memory for generating vanity addresses using the optimization techniques of Elliptic curve operation. Implemented process improvements thatincreased the efficiency of address generation by reducing computation time by up to 30%. Genterated 10 million addresses per seconds on modern CPU architectures / mulitple billions of addresses per second using GPU (CUDA) acceleration | |
| Deepfake Detection | End-to-end pipeline achieving 91.2% accuracy. Deployed as a scalable REST API with Grad-CAM explainability. |    |
| Abnormal Detection | Production-grade anomaly detection using Autoencoders (92.5% precision) with real-time stream analysis. |   |
| Inco Network | Developed privacy-protected L1 blockchain with FHEVM integration for fully homomorphic encryption, enabling private computation on blockchain with Intel SGX remote attestation. |   |
| DeFi Trading Infrastructure | Built high-performance launch pad with sniping functionality and copy trading bots on Solana and Base, optimizing transaction execution using JITO bundles with 40% latency reduction. |   |
Osaka Institute of Technology
Bachelor's Degree (2012-2016) | Master of Science: Computer Science (2016-2017)
- Decentralized AI systems and on-chain ML inference
- AI/ML integration with blockchain infrastructure
- Federated learning and privacy-preserving AI on blockchain