Alireza Sedghi is a senior software engineer and machine learning researcher with nine years of experience building high-performance web-based medical imaging systems and novel ML algorithms for clinical problems. He led architecture and development of Cornerstone3D and OHIF Viewer releases, shipping a WebGL/GPU-based 3D renderer, polymorphic segmentation frameworks, and intelligent hanging protocols that improved radiology workflows at scale. A prolific open-source contributor, he has deep full‑stack experience enhancing cornerstonejs, VTK.js, and DICOM tooling—work that includes advanced annotation tools, shader-level rendering improvements, and performance optimizations for large clinical datasets. His background blends hands-on systems engineering with academic rigor (PhD-level research in medical imaging), including leadership of student teams on deep learning for prostate cancer grading. Based in Toronto, he balances community-driven OSS stewardship with product-focused engineering, and often surfaces non-obvious gains by reducing latency and memory pressure through clever caching and prioritized image loading.
9 years of coding experience
5 years of employment as a software developer
Master of Science (M.Sc.), Bioengineering and Biomedical Engineering, Master of Science (M.Sc.), Bioengineering and Biomedical Engineering at K. N. Toosi University of Technology
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at Queen's University
Cornerstone is a set of JavaScript libraries that can be used to build web-based medical imaging applications. It provides a framework to build radiology applications such as the OHIF Viewer.
Role in this project:
Full-stack Developer
Contributions:1017 releases, 2645 reviews, 489 commits in 1 year 10 months
Contributions summary:Alireza made substantial contributions to the cornerstonejs/cornerstone3d repository, primarily focused on enhancing annotation tools for medical imaging applications. The commits showcase the development and refactoring of several tools like RectangleRoiThreshold, EllipticalRoi, Bidirectional, and CircleScissors tools. These changes involved modifications to core functionality, including the integration of the CPU rendering pipeline, setting up UI for the tools and general maintenance and refactoring for enhanced performance
OHIF zero-footprint DICOM viewer and oncology specific Lesion Tracker, plus shared extension packages
Role in this project:
Front-end Developer
Contributions:515 releases, 2671 reviews, 652 commits in 1 year 8 months
Contributions summary:Alireza primarily focused on enhancing the user interface and functionality of the OHIF viewer. They implemented features for local DICOM drag and drop and incorporated internationalization support for various React components. Furthermore, the user made improvements to the DICOM tag browser and added styling for better user experience. These contributions directly enhanced the viewer's usability and overall user experience.
dicomohifnci-itcrnci-qinquantitative-imaging
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