OC

Jan Hueckelheim

Before joining Argonne, Jan Hückelheim was a postdoc at Imperial College London. He received his PhD degree from Queen Mary University of London in 2017, under the supervision of Jens-Dominik Mueller. His research spans the fields of automatic differentiation, formal software verification, scientific computing, and compilers. He has published in a variety of journals and conferences including ACM Transactions on Mathematical Software, SC, PPoPP, and IPDPS, and contributed to the automatic differentiation tools Tapenade and Enzyme.

Ludger Paehler

Ludger is a sixth-year PhD candidate at TU Munich under the auspices of Nikolaus A. Adams with a MSc in Applied Mathematic from Imperial College London. He is interested in new approaches to composability between simulations and machine learning techniques with an eye toward enabling more affordable workflows for Scientific Machine Learning, Uncertainty Quantification, and Statistical inference. For this he expansively builds on the LLVM, and MLIR toolchain for compiler-based automatic differentiation with Enzyme, and specialized JIT’ing for simulations with jax.infer.