3 Talks: Remote Haskell; Prototyping for Radar; Pure TensorFlow Combinators

Talk 1: Running Haskell functions remotely: Introducing distributed-fork
Speaker: Utku Demir
Description: Utku is going to give a quick introduction to the inner workings of distributed-haskell, and then introduce a small library he wrote called "distributed-fork"; which uses the same mechanism to run arbitrary IO actions on AWS Lambda. ( https://github.com/utdemir/distributed-fork ). (Note: slight change of wording since originally posted due to renaming of library.)

Talk 2: Prototype Driven Development–using Haskell for Radar Tracking
Speaker: Rohit Grover
Description: A high-level view of radar target-tracking. In particular, we will explore how tracking has benefited from a prototype-first approach using Haskell. We find that the use of Haskell allows expressing logic and mathematics succinctly, and we've benefited from using it for system modeling and prototyping. We'd like to share how we work on tracking, and we hope to show a lot of pictures to keep you interested.
Bio: Rohit has been a systems programmer using C/C++ for kernels and embedded systems for the past 20 years. At his current job at Navico, he is responsible for developing filtering algorithms for radar target tracking. Most of his professional work requires writing modern C++, but he finds himself reaching out to Haskell to write correct code faster.

Talk 3: Pure TensorFlow Combinators
Speaker: Randall Britten
Description: Inspired by Justin Le's blog, https://blog.jle.im/entry/purely-functional-typed-models-1.html, this is an exploration of using pure functional combinators in Haskell to define a variety of deep learning neural network architectures using TensorFlow Haskell (https://github.com/tensorflow/haskell )
Bio: Randall is a Data Scientist and Lead Research Engineer at Orion Health using data science, machine learning and deep learning in the context of health informatics and precision medicine. https://nz.linkedin.com/in/randallbritten