Summary
Praitayini Kanakaraj is an AI research engineer specializing in medical image processing with eight years of experience bridging physics-informed deep learning and clinical integration. Her work includes novel MRI gradient nonlinearity correction methods and DeepN4, a differentiable bias-field correction integrated into DIPY, improving reproducibility of large clinical datasets. She has evaluated AI bias using hyperdimensional computing during an FDA fellowship and designs secure, standardized pipelines to deploy models in radiology workflows. Comfortable across Python, PyTorch, MATLAB and multi-GPU systems, she combines rigorous research—40+ manuscripts and large-scale analyses—with production-focused tools like ONNX, Docker, and DICOM APIs. Notably, she has translated numerical and physics-based insights into practical preprocessing components used by the community, reflecting a rare blend of theoretical rigor and operational impact.
8 years of coding experience
3 years of employment as a software developer
Study Aboard Biomedical/Medical Engineering, Study Aboard Biomedical/Medical Engineering at Colorado State University
Science, Science at Stanes higher secondary school
Master's degree Biomedical informatics, Master's degree Biomedical informatics at Stony Brook University
Bachelor of Engineering (BE) Biomedical/Medical Engineering, Bachelor of Engineering (BE) Biomedical/Medical Engineering at PSG College of Technology
Stude Aboard Biomedical engineering, Stude Aboard Biomedical engineering at Flinders University
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at Vanderbilt University
English, Tamil, Telugu