Benjamin Szymkow is a founder and CEO with seven years focused on privacy-preserving AI, building practical data pipelines and governance that enable machine learning without compromising ethics or customer trust. He blends hands-on engineering—contributing to OpenMined’s PyDP Python differential privacy bindings—with operational leadership in open-source research communities and startup product strategy. Ben has led teams tackling homomorphic encryption, federated learning and secure multiparty compute while negotiating data exchange and usage agreements with universities and big tech partners. Based in Perth, he draws on a background in consultancy and CTO roles to translate cutting-edge privacy theory into deployable solutions for regulated industries. Notably, his work emphasizes that business value rests on “good data,” and he focuses on unblocking that value by making private data usable rather than simply locked down.
The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy
Role in this project:
Back-end Developer
Contributions:70 commits, 63 PRs, 54 pushes in 11 months
Contributions summary:Benjamin's contributions primarily involve the development of a Python extension for Google's Differential Privacy library, focusing on building the core module structure. They worked on setting up the build process using `pybind11` and Bazel, creating the necessary bindings for the base status and statusor functionality. Furthermore, the user is integrating the canonical errors and logging functionality into the library, laying the foundation for the core building blocks of the Python wrapper.
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