Tim Siebert
I am a mathematics student in the Master's program at the TU-Berlin and will graduate in spring 2024. In my master's thesis I am working on algorithmic differentiation. Part of the thesis is the development of the ADOLC.jl package, together with Andrea Walther and Jürgen Fuhrmann.
As a student assistant in the Remote Sensing Image Analysis group at the Department of Computer Science at the TU, I have already gained experience in training deep learning models in Python. A year ago, I came into contact with Julia through Jürgen Fuhrmann as part of a TU course. I am currently working at the Weierstrass Institute - Berlin as a student assistant.
My interests are the combination of mathematical theory and software development.
Session
In the Julia community, there are a lot of packages specialized for single (i.e. not combined) methods of algorithmic differentiation (AD), like the well-known ForwardDiff.jl or ReverseDiff.jl. In contrast, the ADOL-C (https://github.com/coin-or/ADOL-C) package was aimed to build a general purpose AD package, which was originally written in C/C++. The newly developed package ADOLC.jl combines the various functionalities of ADOL-C with the convenient usability of Julia.