Machine Learning Engineer

AI/ML Development Boston, Massachusetts, United States

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Summary

Significant Work Experience:
1. ML Research Intern (Massachusetts General Hospital): Implemented a self-supervised denoising network to denoise MRI scans using Bernoulli sampled instances of the scans (the work helped in reducing the time required for patients to complete an MRI scan)
Tested the model for PSNR value comparison with supervised image denoising models and additive gaussian noise to find similar, and at times better performance.
Tested a CNN based model to reconstruct raw MRI scans based on the Blip Up-Down Acquisition (BUDA) reconstruction technique

Expectations

To learn standard practices in training and deploying ML models, contribute in building, training, testing and deploying ML models through Supervised, Unsupervised as well as Self-supervised models.