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Put AI to work
8-9 Oct 2018: Training
9-11 Oct 2018: Tutorials & Conference
London, UK
Ryan Micallef

Ryan Micallef
Research Engineer, Cloudera Fast Forward Labs

Ryan Micallef is a research engineer at Cloudera Fast Forward Labs focused on studying emerging machine learning technologies and helping clients apply them. Ryan is also an attorney barred in New York and spent nearly a decade as an intellectual property litigator focused on technical cases. Ryan holds a bachelor’s degree in computer science from Georgia Tech and a JD from Brooklyn Law School. He spends his free time soldering circuits and wrenching motorcycles. He also teaches microcontroller programming at his local hackerspace, NYC Resistor.


11:55–12:35 Wednesday, 10 October 2018
Models and Methods
Location: King's Suite - Balmoral
Secondary topics:  Deep Learning models, Ethics, Privacy, and Security
Ryan Micallef (Cloudera Fast Forward Labs)
Average rating: ****.
(4.00, 1 rating)
Imagine building a model whose training data is collected on edge devices such as cell phones or sensors. Each device collects data unlike any other, and the data cannot leave the device because of privacy concerns or unreliable network access. This challenging situation is known as federated learning. Ryan Micallef discusses the algorithmic solutions and the product opportunities. Read more.
11:05–11:45 Thursday, 11 October 2018
Models and Methods
Location: Hilton Meeting Room 3-6
Secondary topics:  Media, Marketing, Advertising, Text, Language, and Speech
Ryan Micallef (Cloudera Fast Forward Labs)
Multitask learning is an approach to problem solving that allows supervised algorithms to master more than one objective in parallel. Ryan Micallef shares a multitask neural net in PyTorch trained to classify news from several publications, which highlights distinct language use per publication enabled by the analysis of task-specific and agnostic representations part of multitask networks. Read more.