Shreyas Fadnavis is an AI leader applying machine learning and applied mathematics to medical imaging and computational imaging problems. With 9 years of experience, he currently leads AI at Bioscope AI in Needham, Massachusetts, after guiding AI efforts at Hologic and conducting advanced research at J&J Innovative Medicine and several universities. He specializes in diffusion MRI, 3D/4D imaging, and multimodal vision, having contributed to DIPY's MSMT-CSD and IVIM modeling, and integrating segmentation with HMRF. An active open-source contributor, his work with Diffusion Imaging in Python and GSoC projects demonstrates a hands-on ability to translate theory into robust tooling. He holds a PhD in Intelligent Systems Engineering, Neuroengineering, and Machine Learning from Indiana University Bloomington, with postdoctoral fellowships at Harvard and Harvard Medical School. Based in the Boston area, he blends academic depth with industry leadership to deliver scalable AI solutions in healthcare.
9 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Intelligent Systems Engineering, Neuroengineering, Machine Learning, Doctor of Philosophy - PhD, Intelligent Systems Engineering, Neuroengineering, Machine Learning at Indiana University Bloomington
Bachelor of Engineering - BE, Computer Science, 9 / 10, Bachelor of Engineering - BE, Computer Science, 9 / 10 at Pune Institute of Computer Technology
SSC, Junior High/Intermediate/Middle School Education and Teaching, SSC, Junior High/Intermediate/Middle School Education and Teaching at Loyola High School & Junior College Pune
Higher Secondary Certificate, Bifocal, Computer Science (HSC), Higher Secondary Certificate, Bifocal, Computer Science (HSC) at Fergusson College
Postdoctoral Fellow, Multimodal Machine Learning and Computational Imaging, Postdoctoral Fellow, Multimodal Machine Learning and Computational Imaging at Harvard University
DIPY is the paragon 3D/4D+ medical imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.
Role in this project:
Data Scientist
Contributions:25 reviews, 234 commits, 54 PRs in 4 years 8 months
Contributions summary:Shreyas primarily contributed to the development and testing of a multi-shell constrained spherical deconvolution (MSMT-CSD) model, focusing on the implementation of an IVIM model for multi-shell data denoising and analysis. They made several modifications to the existing MSMT-CSD code by including features like the segmentation using Hidden Markov Random Fields (HMRF) classifier, calculating the mean diffusivity and fractional anisotropy based on the DTI model, and integrating the new IVIM model to improve the model fitting for the diffusion data. The user updated the example code and fixed various issues.
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