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MetisFL is a federated learning framework that allows developers to easily federate their machine learning workflows and train their models across distributed data silos without ever collecting the data in a centralized location. The core of the framework is written in C++ and focuses on scalability, speed and resiliency.

Home Page: https://nevron.ai

License: Other

Shell 0.71% C++ 54.76% Python 38.65% C 0.33% Dockerfile 0.32% Starlark 5.24%

metisfl's Introduction

Hi there ๐Ÿ‘‹

I am currently as a research engineer at Corpy.

My research interests lie at the intersection of machine learning and computational neuroscience. My focus is two-fold:

  1. Developing new methods for analyzing and interpreting neural datasets.
  2. Drawing inspiration from biological brains to design novel architectures and methods

More broadly, I am interested in using machine learning as a tool to elucidate the mechanisms that drive biological and artificial intelligence. For this, I believe modern paradigms such as self-supervised learning, multi-modal learning, and continual learning could offer invaluable insight into the mechanisms of learning.

Apart from my research, I am a core maintainer for Torchmetrics and a core contributor for PyTorch Lightning Bolts.

I previously worked at the Computational Vascular Biomechanics Lab as a PhD pre-candadiate in Biomedical Engineering at the University of Michigan, Ann Arbor. Before that, I completed my MS in Mechanical Engineering at the University of Minnesota, Twin Cities where I researched the computational phenotyping of thoracic aortic aneurysms in the Barocas Lab. I received my BS in Mechanical and Biomedical Engineering from Worcester Polytechnic Institute.

metisfl's People

Contributors

ariskyriakis avatar asfasdfsa avatar canast02 avatar eltociear avatar manobharathi93 avatar panoskyriakis avatar pkyriakis avatar stripeli avatar

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