Principal Computer Vision Engineer at Tetra Bio Distributed
Los Angeles Metropolitan Area United States
Join Prog.AI to see contacts
Join Prog.AI to see contacts
Summary
👤
Senior
🎓
Top School
Mark Roden is a Principal Computer Vision Engineer and seasoned data science leader with 15+ years delivering production ML systems and over 20 years working in image processing, real-time data, and biomedical imaging. He has led teams across live events, healthcare, and microscopy to build high-performance recommendation, fraud-detection, and image-segmentation systems that have served hundreds of millions of users. Trained in biomedical engineering (PhD, UCLA) and with a background in biology and CS from Carnegie Mellon, he blends rigorous academic research with pragmatic engineering. Mark co-founded medical imaging startups and runs a nonprofit that produces open-source medical devices, underscoring a commitment to practical, ethical solutions in healthcare. He’s an active back-end contributor to landmark open-source imaging projects such as ITK/GDCM, improving DICOM handling and code robustness. Known for shipping ultra-low-latency recommendation pipelines and productionized ML at scale, he pairs deep technical craftsmanship with cross-disciplinary leadership.
15 years of coding experience
21 years of employment as a software developer
University of California, Los Angeles
Bachelor's Degree, Biology, minor in Computer Science, Bachelor's Degree, Biology, minor in Computer Science at Carnegie Mellon University
french (can get by, but will need a week or two of immersion), czech (extremely basic), Spanish
Grassroots DICOM read-only mirror. Only for Pull Request. Please report bug at http://sf.net/p/gdcm
Role in this project:
Back-end Developer
Contributions:284 commits in 1 year 9 months
Contributions summary:Mark primarily focused on fixing warning messages within the project's anonymizer. Their contributions involved code changes in the `gdcmAnonymizer.cxx` and `gdcmAnonymizeEvent.h` files, addressing issues related to size warnings and type casting to avoid potential errors. Furthermore, the user made efforts to optimize the code by handling pointer differences correctly. They also focused on maintaining code quality by removing unused variables and adapting code to win64.
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:
Back-end Developer
Contributions:21 commits in 7 months
Contributions summary:Mark primarily focused on fixing warnings and addressing potential issues within the GDCM library, which is a part of the ITK project. Their commits involve modifications to the `gdcm` utilities, specifically concerning data structures, file formats, and codecs (JPEG, RLE, JPEG2000). These changes aimed at improving code quality, preventing potential build failures, and ensuring the correct handling of DICOM data, demonstrating a focus on the back-end aspects of image data processing.
pythonitkcomputer-visionopen-sciencescientific
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
Mark Roden - Principal Computer Vision Engineer at Tetra Bio Distributed