October 28–31, 2019
Jason Mancuso

Jason Mancuso
Research Scientist, Dropout Labs


Jason Mancuso is a research scientist at Dropout Labs, the founder of Cleveland AI, and an active member of the AI Village at DEF CON and the OpenMined community. He works on novel methods of making machine learning more performant for privacy-preserving techniques, most notably by contributing to the TF Encrypted project. He’s worked on a variety of safety and security problems, including safe reinforcement learning, secure and verifiable agent auditing, and neural network robustness. His work with the Cleveland Clinic established a state-of-the-art blood test classification and demonstrated that machine learning can virtually eliminate the problem of medical malpractice due to contaminated blood samples.


1:30pm5:00pm Tuesday, October 29, 2019
Location: Grand Ballroom G
Jason Mancuso (Dropout Labs), Yann Dupis (Dropout Labs)
Average rating: ****.
(4.00, 1 rating)
Jason Mancuso and Yann Dupis demonstrate how to build and deploy privacy-preserving machine learning models using TF Encrypted, PySyft-TensorFlow, and the TensorFlow ecosystem. Read more.
  • O'Reilly
  • TensorFlow
  • Google Cloud
  • IBM
  • Databricks
  • Tensor Networks
  • VMware
  • Amazon Web Services
  • One Convergence
  • Quantiphi
  • Lambda Labs
  • Tech Mahindra
  • cnvrg.io
  • Determined AI
  • Inferencery
  • Manceps, Inc.
  • PerceptiLabs
  • Valohai

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