Education
BEng in Biomedical Engineering, Manipal University, India, 2010
MSc in Biomedical Computing, Technical University of Munich, Germany, 2014
Titles and Appointments
Software Architect
Address
HITS Building
410 W 10th Street
Indianapolis, IN 46202
Research Keywords
Privacy aware machine learning, clinical workflows, reproducibility
Links
Google Scholar
LinkedIn
Twitter
GitHub
Professional Organizations/Memberships
MICCAI Society
Research Summary/Bio
My research interest focuses on machine learning and the application of distributed and privacy-protected computational algorithms to solve problems pertaining to medical imaging. My work has spanned across the areas of robotics, machine learning, histopathology, and image processing applied to medical imaging data. I believe that open-source software fosters better science, and thus have been involved in multiple open-source projects and their associated research studies, including the Federated Tumor Segmentation (FeTS) platform and the Cancer Imaging Phenomics Toolkit (CaPTk). I am currently focusing my efforts on the Federated Learning for Postoperative Segmentation of Treated glioblastoma (FL-PoST), the Generally Nuanced Deep Learning Framework (GaNDLF), MedPerf for federated algorithmic benchmarking, and the Open Federated Learning (OpenFL) library. You can find more information about me on my personal page: https://sarthakpati.github.io