Ulf Schiller
Associate Professor
Newark, Delaware, United States
Summary
👤
Senior🎓
Top SchoolUlf Schiller is an Associate Professor and computational physicist with 20 years of experience developing high-performance simulation methods for soft matter, hydrodynamics and biophysics. He designs and implements novel multiscale algorithms, with practical expertise in parallel and GPU-accelerated computing applied to hemorheology and hemodynamics. A long-term contributor to the widely used ESPResSo molecular dynamics package, he has improved core parallel communicators, MPI derived datatype support and refactored lattice-Boltzmann GPU kernels. His background blends physics and computer science (Diplomas in Physics and Informatics, Dr. rer.-nat.), enabling him to bridge theoretical modeling and production-quality code. He has held research and faculty positions across leading institutions in Europe and the US, bringing both deep numerical insight and hands-on software engineering to interdisciplinary problems. Beyond simulations, he leverages machine learning tools to augment multiscale models, reflecting a practical interest in hybrid physics–AI workflows.
20 years of coding experience
14 years of employment as a software developer
Dr. rer.-nat., Dr. rer.-nat. at Johannes Gutenberg University MainzDipl.-Phys., Dipl.-Phys. at Bielefeld University
German, English, Dutch, Spanish, French
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (9)
mpi10
cpp10
physics10
molecular-dynamics-simulation10
cplus10
molecular-simulation10
scientific-computing10
dynamics10
decomposition9
Programming languages (6)
Github contributions (5)
espressomd/espresso
Mar 2006 - Sep 2020
The ESPResSo package
Role in this project:
Back-end Developer
Back-end DeveloperContributions:82 commits, 1 PR, 23 comments in 14 years 8 months
Contributions summary:Ulf primarily focused on improving the core functionality of the ESPResSo package, a molecular dynamics simulation software. Their contributions include implementing communicators for temporary particle data, crucial for random number generation, and fixing bugs related to periodic boundary conditions. They also added support for derived datatypes in the MPI implementation, which is essential for parallel computing. Furthermore, the user refactored and updated the LB scheme and its GPU implementation.
physicssoft-matterpythonmolecular-dynamicsscientific-computing
Clemson-MSE/espresso
Sep 2016 - Jun 2022
Contributions:2 PRs, 2 pushes, 1 branch in 5 years 9 months
espressoesp32
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