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tuhoag/README.md
  • ๐Ÿ‘‹ Hi, Iโ€™m Tu Hoang, a Postdoctoral Researcher at the Hamburg University of Technology.
  • ๐Ÿ‘€ Iโ€™m interested in Privacy and Security for Machine Learning/Deep Learning and Decentralized Systems.
  • ๐ŸŒฑ Iโ€™m currently working on privacy-preserving technologies: anonymity (k-anonymity, differential privacy) of knowledge graphs, zero-knowledge proof protocols for blockchain-based applications (proximity marketing, data publishing), and privacy-preserving distributed learning (differential privacy).
  • ๐Ÿ’ž๏ธ Iโ€™m looking to collaborate on privacy-preserving technologies for machine learning/deep learning and decentralized systems.
  • ๐Ÿ“ซ Feel free to reach me at contact@tuhoang.me.

Pinned Loading

  1. zkSSI zkSSI Public

    A zero-knowledge self-sovereign identity framework enables verifying attribute-based access control policies on-chain and off-chain.

    TypeScript

  2. personalized-anony-kg personalized-anony-kg Public

    An algorithm generates k-anonymous knowledge graphs while protecting users' privacy with their own privacy preferences and maximizing their quality for knowledge graph learning.

    Python

  3. promark promark Public

    A zero-knowledge and transparent proximity marketing platform using Hyperledger Fabric.

    Go

  4. sequential-anonygraph sequential-anonygraph Public

    Python

  5. elliptic-curve-cryptography-go elliptic-curve-cryptography-go Public

    Go