Aneesh Rangnekar
Senior AI Scientist - Computational Radiology
Boston, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolAneesh Rangnekar is a research fellow in New York with nine years of experience building safe, reliable vision and multimodal models for medical imaging and related domains. He specializes in self-supervised pretraining and parameter-efficient post-training (LoRA/DoRA and frozen feature augmentation) to improve out-of-distribution detection and robustness under distribution shift, cutting fine-tuning GPU hours by ~30% in deployed segmentation workflows. At Memorial Sloan Kettering he led large-scale curation and distributed pretraining on multihospital CT/MRI/PET and language data and collaborated closely with clinicians to move models into clinical pipelines. His earlier work spans hyperspectral and remote sensing foundation models and scalable 4+TB dataset pipelines, reflecting a blend of rigorous academic training (PhD Imaging Science) and practical production impact. Notably, he applies continual self-supervised strategies across modalities to tackle low-data regimes and real-world OOD challenges.
9 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD Imaging Science, Doctor of Philosophy - PhD Imaging Science at Rochester Institute of Technology
Github Skills (29)
dcgan9
python8
generative-adversarial-network8
image-manipulation8
data-science7
pytorch7
machine-learning7
computer-graphics7
tensorflow7
deep-learning7
image-analysis7
computer-vision6
jax6
image-translation6
parsing5
Programming languages (4)
Github contributions (5)
aneesh3108/AeroRIT
Mar 2020 - May 2021
Accompanying code for the paper 'AeroRIT: AeroRIT: A New Scene for Hyperspectral Image Analysis'
Contributions:7 commits, 2 PRs, 22 pushes in 1 year 2 months
image-analysis
aneesh3108/aneesh3108.github.io
Nov 2021 - Mar 2026
Contributions:26 pushes, 1 branch in 4 years 4 months
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