CASUS – Center for Advanced Systems Understanding

SUSTAINABLE
SYSTEMS
SCIENCE

We combine methods from mathematics, systems theory, data science, and scientific computing with the aim to rethink data-intensive systems research. Based on high-quality research data, we develop digital solutions that are used across disciplines.

Lately at CASUS

Rocket flight workshop

Young people take a rocket (not quite all the way) into space and back to Earth - as part of a engineering and programming workshop at CASUS

Centre for Molecular Water Science inaugurated in Hamburg

Scientists from two HZDR institutes, the Institute for Resource Ecology and CASUS, will contribute to the research efforts.

New catalysts for more sustainability

CASUS scientist receives 1.8 million euros from BMBF “Quantum Future” program

The German Federal Ministry of Education and Research (BMBF) funds research into controlled quantum states of individual or coupled systems with its ongoing emerging talent program “Quantum Future”.

AI approach leverages optics phenomenon to produce better images

CASUS scientist receives prestigious ERC Starting Grant

Young Investigator Dr. Tobias Dornheim aims to tackle one of the fundamental computational bottlenecks in physics, chemistry, and related disciplines.

Tobias Dornheim receives Lem Research Prize

Wrocław University of Science and Technology’s young talent award goes to CASUS researcher

Let's talk about it

Approximation theory & approximation practice pt. 2

12 - 15 May 2025

Scultetus Summer School 2025

The emphasis of the event is on practical and theoretical aspects of approximating and interpolating functions, using high-order polynomials, trigonometric series, and rational functions.

Lem Prize 2024 award ceremony

15 May 2025

External Event

CASUS Young Investigator Tobias Dornheim will be awarded Wrocław University of Science and Technology's Lem Prize in a festive ceremony. Participation is limited.

For a good read

Minterpy: multivariate polynomial interpolation in Python

Damar Wicaksono, Uwe Hernandez Acosta, Sachin Krishnan Thekke Veettil, Jannik Kissinger and Michael Hecht - Journal of Open Source Software 10 (109), 7702 (2025)

Interpolation is essential in various computational tasks, including function approximation, curve fitting, numerical integration, differential geometry, spectral methods, optimization, and uncertainty quantification. Minterpy is an open-source Python package designed for multivariate polynomial interpolation. It provides stable and …

Single exposure quantitative phase imaging with a conventional microscope using diffusion models

Gabriel della Maggiora, Luis Alberto Croquevielle, Harry Horsley, Thomas Heinis, Artur Yakimovich - Proceedings of the AAAI Conference on Artificial Intelligence 39 (3), 2672-2680 (2025)

Phase imaging is gaining importance due to its applications in fields like biomedical imaging and material characterization. In biomedical applications, it can provide quantitative information missing in label-free microscopy modalities. One of the most prominent methods in phase quantification is the Transport-of-Intensity Equation (TIE). TIE often requires multiple acquisitions at different defocus distances, …

Decoding the interaction mediators from landscape-induced spatial patterns

Eduardo Henrique Colombo, Lucianno Defaveri, Celia Anteneodo - Physical Review E 111 (1), 014402 (2025)

Interactions between organisms are mediated by an intricate network of physico-chemical substances and other organisms. Understanding the dynamics of mediators and how they shape the population spatial distribution is key to predict ecological outcomes and how they would be transformed by changes in environmental constraints. However, due to the inherent complexity involved, this task is often unfeasible, from the empirical and …

Probing iron in Earth’s core with molecular-spin dynamics

Svetoslav Nikolov, Kushal Ramakrishna, Andrew Rohskopf, Mani Lokamani, Julien Tranchida, John Carpenter, Attila Cangi, Mitchell A. Wood - PNAS December 12, 2024

Dynamic compression of iron to Earth-core conditions is one of the few ways to gather important elastic and transport properties needed to uncover key mechanisms surrounding the geodynamo effect. Herein, a machine-learned ab initio derived molecular-spin dynamics (MSD) methodology with explicit treatment for longitudinal spin-fluctuations is utilized to probe the dynamic phase-diagram of iron…

Get to know our teams

Theory of Complex Systems

Prof. Thomas D. Kühne

Chemical as well as physical processes are intrinsically associated with large length and time scales.

Earth System Science

Prof. Dr. Justin Calabrese

The Earth System Science research team at CASUS tackles problems at the interface spatial ecology, hydrology, and anthropogenic change to understand the dynamics of biodiversity in the Anthropocene

Machine Learning for Materials Design

Dr. Attila Cangi

We develop scalable machine learning frameworks to improve density functional theory simulations, connect microscopic and mesoscopic simulations, and model advanced material properties.

Frontiers of Computational Quantum Many-Body

Dr. Tobias Dornheim

Our group develops novel methods and concepts to tackle problems from quantum many-body theory.

Scientific Computing Core

Dr. Andreas Knüpfer

The department supports CASUS researchers in all aspects of scientific computing and data-driven research. It also conducts research on specific topics of its own.

Computational Radiation Physics

Dr. Michael Bussmann

The group models, simulates and visualizes the dynamics of particles and radiation phenomena that are of interest when investigating the physics of laser particle acceleration.

AI 4 Quantum

Dr. Werner Dobrautz

We develop a synergistic high-performance and quantum computing approach aided by novel artificial intelligence/deep machine learning methods to enable the computational study of complex quantum systems relevant to the green energy transition.

Theoretical Chemistry

Dr. Agnieszka Beata Kuc

In the Theoretical Chemistry group, we explore innovative materials, with a particular emphasis on two-dimensional systems, for use in energy storage and generation, catalysis, isotope separation, and nano(opto)electronic devices.

We are not making science for science

We are making science for the benefit of humanity

Françoise Barré-Sinoussi

Mathematical Foundations of Complex System Science

Dr. Michael Hecht

The beauty and fascinating enigmatic nature that complex systems embody might be the driving force behind the ambitions of many scientists in their realm of scientific research.

Dynamics of Complex Living Systems

Dr. Ricardo Martínez-García

In the Dynamics of Complex Living systems team, we are interested in standing self-organization and emergence in living systems across scales.

Machine Learning for Infection and Disease

Dr. Artur Yakimovich

Machine Learning for Infection and Disease (MLID) group aims to develop novel computational methods to facilitate our understanding of Infection Biology and Disease Biology.