Ziv Yaniv is an experienced researcher and software engineer specializing in bio-medical image analysis, machine learning, and augmented/mixed reality, with over 20 years in algorithmic research and software development. He founded Yaniv Research LLC and consults for small and mid-sized companies developing image-analysis algorithms and image-guided navigation tools, while also serving as Senior Imaging Scientist at NIAID. Ziv has a strong track record in open-source scientific software—making substantial back-end and QA contributions to flagship projects like ITK and SimpleITK, improving IO robustness, registration accuracy, and documentation. His work crosses academic and clinical boundaries, informed by deep familiarity with microscopy workflows and real-world intervention practices. Holding a PhD in Computer Science from The Hebrew University of Jerusalem, he pairs rigorous research with practical engineering to deliver solutions that integrate smoothly into established domain practices. An often-overlooked strength is his long-term focus on reproducible, tested code in complex imaging pipelines, reflected in numerous targeted fixes and added tests across major repositories.
11 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at The Hebrew University of Jerusalem
SimpleITK: a layer built on top of the Insight Toolkit (ITK), intended to simplify and facilitate ITK's use in rapid prototyping, education and interpreted languages.
Role in this project:
Back-end Developer
Contributions:7 releases, 461 reviews, 152 commits in 8 years 3 months
Contributions summary:Ziv made multiple contributions to the SimpleITK library, primarily focused on improving its core functionality and fixing existing bugs. Their work involved modifying CMake configurations to ensure the correct ITK module dependencies, correcting translation vectors, and adding constructors to global transformations. The user also addressed issues related to the ImageSeriesReader and ImageSeriesWriter, improving the robustness of the IO operations, and improved the documentation for the read image interfaces. The user further contributed to the test suite with the addition of multiple tests.
Insight Toolkit (ITK) -- Official Repository. ITK builds on a proven, spatially-oriented architecture for processing, segmentation, and registration of scientific images in two, three, or more dimensions.
Role in this project:
Backend Developer & QA Engineer
Contributions:26 reviews, 21 commits, 36 PRs in 7 years 8 months
Contributions summary:Ziv primarily focused on fixing bugs and improving code quality within the ITK library. Their contributions include addressing compiler warnings, making implicit casts explicit, and correcting errors in image processing and registration modules. They also implemented tests to identify and resolve issues related to image transformation, particularly in the context of Euler angles, landmark-based initialization, and file format handling (e.g., NIFTI and VTK). Furthermore, the user fixed the `SetLabelForUndecidedPixels` value.
pythonitkcomputer-visionopen-sciencescientific
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