Federated Learning Webinar

Using federated learning to build intelligent healthcare systems without moving data.

When: Tuesday, June 9, 2020, at 9 AM PST
Where:
Webinar via Zoom
Length:
60 minutes

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Program

Topics:
- Federated learning infrastructure
- Privacy health research for both cloud and edge learning

Use cases with applications for:
- Distributed mobile-based A.I. training for images
- Edge computing for DNA information
- Edge computing for immunovigilance using unique health signatures
- Federated cloud learning on real-world data

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Co-hosts

Sam De Brouwer
Co founder, doc.ai
Akshay Sharma
CTO, doc.ai

Presenters

A group of federated learning engineers at doc.ai will present during this webinar then answer direct questions from the audience.

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Overview &
why you should attend

Our team at doc.ai, a Palo Alto-based deep learning company, has made significant advances in federated learning and other privacy-preserving techniques in healthcare applications to build intelligent systems without moving data.

Federated learning provides an inroad to sharing machine learning models without sharing the underlying data used to train these models. The technique helps us learn from privacy-sensitive data on edge devices.

Our first work in federated learning was presented last December at the Neurips conference by Philip Dow, head of mobile federated learning at doc.ai. 

Our tech stack

Power your real-time decisions for better health outcomes.

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About doc.ai

We accelerate better health outcomes for current and future generations.

Learn more

Privacy and security are the core values of our healthcare interactions. The decentralization of the learning on the edge is imperative to serve those values.

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