Dmitrii Usynin is a Senior Privacy Researcher based in Munich with 15 years of experience at the intersection of secure computing, privacy-preserving ML and decentralisation. He blends academic rigor from a joint PhD program (Imperial College / TUM) and hands-on industry research at Huawei, Microsoft Research, Brave and OpenMined, focusing on differential privacy, federated learning and secure enclaves for LLMs and healthcare data. Dmitrii has translated research into practice—building DP training frameworks, privacy-preserving synthetic data pipelines and automation tooling for trusted deployments—and has experience improving CI/CD and container workflows in notable open-source projects. He also brings a strategic lens from venture investing at Creator Fund, sourcing deep-tech startups while maintaining active research contributions to Flashbots and other privacy-focused communities. Notably, his work spans both agentic LLM security and non-IID federated systems, demonstrating a rare combination of theoretical depth and production-focused engineering.
14 years of coding experience
5 years of employment as a software developer
High school, High school at Cheltenham College
PhD Privacy in Medical Machine Learning, PhD Privacy in Medical Machine Learning at Imperial College London
PhD Privacy in Medical Machine Learning, PhD Privacy in Medical Machine Learning at Technical University of Munich
Secondary education Linguistics and Informatics, Secondary education Linguistics and Informatics at Lyceum 11
chroot, mount --bind, and binfmt_misc without privilege/setup for Linux
Role in this project:
DevOps Engineer & Automation Engineer
Contributions:11 commits, 11 PRs, 24 pushes in 2 years 1 month
Contributions summary:Dmitrii primarily focused on improving the project's build and deployment processes. This involved updating the Travis CI configuration, including building and validating the CARE archive. The commits also addressed build failures, badge URL updates, and integrating static builds after successful builds. Furthermore, the user implemented and added scripts for re-archiving and converting CARE archives to Docker images, demonstrating a focus on automation and streamlining project workflows.
A Scala SDK for the iExec decentralised computing platform
Contributions:40 commits, 1 PR, 16 pushes in 5 months
blockchainsdkscaladecentralisedcomputing
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.
Request Free Trial
Dmitrii Usynin - Senior Privacy Researcher at Huawei