Experienced Solutions provider & AI Researcher and Vice Chair for Algorithm Development and Benchmarking at the Medical Working Group of MLCommons working on designing solutions for various domains.
I believe open 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 following:
- Federated Learning for Postoperative Segmentation of Treated glioblastoma (FL-PoST)
- Generally Nuanced Deep Learning Framework (GaNDLF)
- MedPerf
- Open Federated Learning (OpenFL) framework
- Creating and maintaining as many Anaconda recipes as possible to maximize reproducibility and scientific impact of open-source software
- Applying concepts of AI (with a focus on privacy) to solve problems in healthcare.
- Committed to doing reproducible and deployable research.
- Firm believer of the saying a weak algorithm that is well written & integrated is better than a strong algorithm that isn't.
- Advocating for F.A.I.R. in research.
- Helping people choose the correct career path.