MuniHac is a three day Haskell hackathon taking place from Friday 16th to Sunday 18th November 2018 in the beautiful city of Munich, hosted and sponsored by TNG Technology Consulting GmbH and co-organized by Well-Typed LLP. The Hackathon is intended to follow the tradition of other Haskell Hackathons such as the ZuriHac, HacBerlin, UHac and many others.
We have capacity for ~80 Haskellers to collaborate on any Haskell-related project they like. There will be beginner workshops and a mentor program to help you get started. Of course you can as well start hacking Haskell right away. Anyone is welcome to participate. Beginner or pro, we've got you covered :)
Hacking on Haskell projects will be the main focus of the event, but we will also have a couple of talks by renowned Haskellers. The MuniHac is furthermore a great opportunity to meet and socialize with fellow Haskellers and have a great time together. Among other things, we are looking forward to having BBQ, pizza and a traditional Weißwurstfrühstück.
Ryan is a Ph.D student at Indiana University, where he
attempts to combine techniques from software verification and
determinism (sometimes successfully!). He is also a key
contributor to GHC, where he specializes in the areas of
deriving, Template Haskell, pattern-match coverage
checking, and various odds and ends in the typechecker. Through a
series of strange coincidences, he is also a member of the Haskell
Core Libraries Committee and maintains libraries ranging from
Ben uses Haskell in fields as diverse as applied machine learning, scientific data analysis, robotics control, and compiler engineering. He is an active contributor to the Glasgow Haskell Compiler with focus on code generation, Core optimization, and the runtime system, and has worked extensively towards bringing GHC to the ARM architecture.
He has experience implementing numerical methods for machine learning, with an eye towards leveraging Haskell’s strong type system to enforce correctness at compile-time. Ben has expertise developing high-performance distributed systems in a wide range of languages. Past projects include GPU-based modelling of high-energy particle interactions and an implementation of parallel machine learning algorithms for large-scale social network analysis.
He is completing a PhD in Physics at the University of Massachusetts and has publications spanning social network analysis, computational physics, and biophysics.
Matthew is a PhD student at the University of Bristol focusing on program generation with applications to optimisation. In the quest to write the perfect program he has become a regular contributor to GHC where he has recently been working on making the compiler easier to extend by using source plugins.
A few suggestions to help you find a hotel.