Lorenz Hofmann-wellenhof is a software engineer with nine years of experience building data-driven products and backend systems, currently working on Cresta Insights. He has a strong academic foundation in computer science (MSc, Universität Passau) and practical exposure from a Google Summer of Code project that produced gnostic-grpc, reflecting comfort with API tooling and compiler-like models. Lorenz contributes to prominent open-source projects in ML security—implementing FGM, PGD and SPSA attacks for CleverHans—demonstrating expertise in adversarial example generation and TensorFlow 2.0 migration. His industry experience spans B2B microservices for retail banking and lifecycle management systems for universities, showing an ability to move research ideas into production. Based in Dubai with roots in Berlin, he pairs a sporty, growth-oriented mindset with a taste for Korean BBQ—an understated hint at his collaborative and approachable working style.
9 years of coding experience
4 years of employment as a software developer
Computer Science, Exchange semester, Grade: 4.0 (GPA), Computer Science, Exchange semester, Grade: 4.0 (GPA) at Stevens Institute of Technology
Bachelor of Science - BS, Mobile und Eingebettete Systeme, Grade: 1.8 (German system) ~ 3.2 (GPA), Bachelor of Science - BS, Mobile und Eingebettete Systeme, Grade: 1.8 (German system) ~ 3.2 (GPA) at Universität Passau
A compiler for APIs described by the OpenAPI Specification with plugins for code generation and other API support tasks.
Role in this project:
Back-end Developer
Contributions:11 commits, 13 PRs, 50 comments in 2 years 6 months
Contributions summary:Lorenz primarily focused on enhancing the surface model for the OpenAPI specification compiler. Their work involved building types from OpenAPI component sections and reference objects, specifically for parameters, request bodies, and responses. They implemented changes to handle `oneOf`, `anyOf`, and `allOf` sub-schemas, and added support for enum values and enum arrays. The user's contributions improved the accuracy and completeness of the model used for code generation.
An adversarial example library for constructing attacks, building defenses, and benchmarking both
Role in this project:
ML Engineer
Contributions:12 commits, 2 PRs, 4 comments in 25 days
Contributions summary:Lorenz primarily contributed to the implementation of machine learning algorithms within the CleverHans library, specifically focusing on the integration of Fast Gradient Method (FGM) and Projected Gradient Descent (PGD) attacks for TensorFlow 2.0. Their work also includes refactoring utility functions and adapting the SPSA (Simultaneous Perturbation Stochastic Approximation) attack to the TF2 environment. These changes demonstrate a focus on building and refining adversarial example generation methods.
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Lorenz Hofmann-wellenhof - Software Engineer at Cresta