Lars is a pure mathematician by training, and holds a PhD in the same. He has spent several years teaching and doing postgraduate research in arithmetic number theory at Cambridge University in the UK, and at Regensburg University in Germany. He worked for ten years as a Lead Software Architect for an international IT company. His job, amongst other things, was the application of mathematical optimization techniques to the paper industry and web framework development (using mostly C#, JavaScript and TypeScript). His present position is that of Director of Education at Input Output Hong Kong (IOHK), working on blockchain technology and teaching Haskell and other subjects. He has been interested in programming since his early teens, and he loves learning new programming languages and paradigms - in particular those that offer a radically new way of looking at problems and of thinking about solutions. He is especially fascinated by functional programming and its promise of elegant, bug-free code that can be developed rapidly.
Talks I've Given
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This Ain't Your Daddy's Probability Monad - Modelling Probabilistic Time in Haskell
Featuring Lars Brünjes
It is well known that (discrete) probability distributions can be implemented as monads in Haskell in various more or less sophisticated ways.
haskell network-modelling time probability monad -
Authenticated Data Structures, Generically, in Haskell
Featuring Lars Brünjes
"An authenticated data structure (ADS) is a data structure whose operations can be carried out by an untrusted prover, the results of which a verifier can efficiently check as authentic." (Andrew Miller et al.)
haskell data-structures free-monads cryptographic-hash-function interpreters-for-free-monads authenticated-data-structures -
Lightning Talk: Protop--Dependent Types through Topoi
Featuring Lars Brünjes
The idea of this talk is to take a somewhat unusual route to dependent types, not via type-theory, but rather by trying to model a "topos" in Haskell. A "topos" is a special kind of category which is basically a theory of sets that makes it possible to do most of the usual...
haskell types -
Neural Nets with Automatic Differentiation
Featuring Lars Brünjes
During this talk, you will learn how to use Haskell's powerful features for abstraction to create a Neural Network library in native Haskell that makes it easy to create complex network architectures in a type-safe and flexible way.
Automatic differentiation is used to provide painless...
haskell haskellx neural nets api differentiation
My Work
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Social and Blogging
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