January 12 - April 17, 2026

Description: Many scientific and engineering problems exhibit a combination of complex interactions over wide ranges of scales and input data parametrized over high-dimensional parameters spaces.  However, naive applications of numerical solution techniques to such problems are often beyond current computational feasibility. To this end, multilevel, multifidelity, and multiscale problems have emerged as innovative approaches which can be applied to a wide range of processes in scientific and engineering domains. They can enhance simulation-based modeling, uncertainty quantification, optimization and design, inverse problems, and data assimilation. The Junior Trimester Program aims to foster the development of a new generation of efficient numerical methods and their numerical analysis by cross-fertilizing methods from multifidelity, multilevel and multiscale techniques. For this, it will bring together junior researchers from the corresponding communities to build new bridges between the different methods.

The online application platform to participate in this trimester program is open until June 15, 2025 (CET).

Click here to access the application platform.

In case of questions concerning services and administration, please contact Emma Seggewiss or Kanami Ueda (him-contact@hcm.uni-bonn.de or him-coordination@hcm.uni-bonn.de)

January 19 - 23, 2026

Venue: HIM lecture hall, Poppelsdorfer Allee 45, Bonn

Organizers: Steffen W. R. Werner, 

Description: TBA

February 2 - 6, 2026

Venue: HIM lecture hall, Poppelsdorfer Allee 45, Bonn

Organizers: Niklas Baumgarten (Heidelberg University), Tung Le (Carl von Ossietzky Universität Oldenburg), Emil Løvbak (Karlsruhe Institute of Technology), Anastasia Istratuca (University of Edinburgh and Heriot-Watt University), Pieterjan Robbe (Sandia National Laboratories), Linus Seelinger (Karlsruhe Institute of Technology), Tommaso Vanzan (Politecnico di Torino), Steffen W. R. Werner (Virginia Polytechnic Institute and State University)

Description: Many simulation problems contain phenomena at multiple scales of resolution in terms of both space and time. In practice, solving such problems is often challenging due to inherently stochastic model behavior or uncertain parameters, modeled probabilistically. As such, the demand for sophisticated techniques for stochastic simulation and uncertainty quantification (UQ) is growing across scientific and engineering disciplines. Hierarchical methods, which use multilevel and multifidelity approaches, are particularly promising, balancing accuracy and computational efficiency.

In this workshop we invite contributions from researchers working in the following thematic areas:

1. Multilevel and Multifidelity methods: Multilevel and multifidelity strategies judiciously allocate computational resources between expensive high-fidelity models and less costly low-fidelity models. These strategies allow for the efficient computation of low variance/high accuracy results. Hence, efficient simulation and UQ are possible.
2. Multifidelity Surrogate Models: Resource constraints often limit data availability for computationally expensive simulations. Multifidelity surrogate models, such as multifidelity Gaussian processes, chain models with increasing fidelity, balancing error and cost. These surrogates support adaptive sampling strategies, incrementally improving accuracy.
3. Applications of Multifidelity Methods: Multifidelity techniques are applied across disciplines, from fusion energy to climate modeling. This focus area will feature domain experts demonstrating the use of these tools in real-world scenarios, showcasing their ability to provide accurate, reliable UQ. This includes software packages for multifidelity stochastic simulation and UQ.

February 23 - 27, 2026

Venue: HIM lecture hall, Poppelsdorfer Allee 45, Bonn

Organizers: Sara Avesani (Università della Svizzera Italiana), Carles Beall (Stevens Institute of Technology), Moritz Hauck (Karlsruhe Institute of Technology), Maher Khrais (University of Bonn), Dilini Kolombage (Institute for Numerical Simulation, University of Bonn), Roland Maier (Karlsruhe Institute of Technology), Florian Schneider (University of Leipzig), Lucia Swoboda (Chalmers University of Technology and University of Gothenburg), Johan Wärnegård (Chalmers University)

Description: In many applications, classical discretization methods are limited when dealing with heterogeneous microstructures, especially when variations occur over multiple scales. Globally resolving such structures can lead to an intractable number of degrees of freedom, and not resolving them generally leads to incorrect approximations. Problem-adapted approximation spaces provide an elegant solution by effectively bridging scale differences. The goal of this workshop is to explore optimal problem-adapted approximation spaces, their theoretical properties, and their efficient computation. The use of problem-adapted approximation spaces is particularly advantageous in time-dependent or multi-query scenarios, such as statistical analysis, where multiscale constructions can be repeatedly applied to optimize the simulation at coarse scales. Participants will gain insight into recent advances in multiscale methods and have the opportunity to exchange ideas and collaborate with other workshop members and participants of the Junior Trimester Program.

March 9 - 13, 2026 

Venue: HIM lecture hall, Poppelsdorfer Allee 45, Bonn

Organizers: Lucas Bouck (Carnegie Mellon University), Christian Döding (University of Bonn), Benjamin Dörich (Karlsruhe Institute of Technology), Zetao Ma (School of Mathematical Sciences, Shanghai Jiao Tong University), Andres Galindo Olarte (University of Texas at Austin), Christos Pilichos (Uppsala University), Vishnu Raveendran (University of Bonn), Andrea Rupp (Saarland University), Qinchen Song (Shanghai Jiao Tong University)

Description: TBD