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List of Minisymposia

If you are interested in organizing a minisymposium, please send a tentative title and a brief description to esco@fel.zcu.cz.

Applied Statistics and Data Science


  • Anna Panorska (ania@unr.com, University of Nevada, Reno, USA)
  • Warren Davis, Sandia National Laboratories, USA)

The Statistics and Data Science mini symposium will feature new directions in computational and applied statistical and machine learning methods. The aim is to gather researchers and practitioners from various science and engineering areas who use statistical and AI methods to work on applied projects and research questions in diverse areas such as, for example: extreme events, risk, insurance, dependence structures, ecological and epidemiological modeling, or data privacy. The idea is to cross pollinate the research methods and approaches which may be standard in one are, but relatively unknown in other areas. We welcome different applications and new data analysis.

Computers and ICT in Mathematics Education


The increasing use of computers and ICT (Information and Communication Technologies) in every kind of activity (industrial, academic, social, ...), is nowadays a fact that must be addressed. Specifically in Education, the computer and ICT are being used from different point of views in order to develop different Education strategies and techniques (programming, e-learning, blended learning, open and distance learning, learner-centered environments, …). It is very important to know the new trends in the use of Computer and ICT in Education since it is a field in constant evolution. In this minisymposium, proposals dealing with the use of Computers and ICT in Mathematics Education and experiences in online teaching during COVID pandemic are welcome. The minisymposium will promote the outreach of new experiences, application of new educational models and techniques in Mathematics Education in which the use of computers and ICT have a key role.

Advanced Computational Methods for Climate Modeling and Analysis


The development and application of global climate models for understanding and predicting the effects of global climate change and sea-level rise is critical, since it can direct energy and infrastructure planning, as well as inform public policy. Earth System Models (ESMs), which are global climate models including biogeochemistry, integrate the interactions between atmosphere, ocean, land, ice, and biosphere to enable the simulation of the state of regional and global climate under a wide variety of conditions. In recent years, there has been a push to develop “next generation” ESMs, models which: (1) are able to perform realistic, high-resolution, continental scale simulations, (2) are robust, efficient and scalable on next-generation hybrid systems (multi-core, many-core, GPU) towards achieving exascale performance, and (3) possess built-in advanced analysis capabilities (e.g., sensitivity analysis, optimization, uncertainty quantification).

This minisymposium will consist of talks describing new and ongoing research in the development of accurate and tractable “next-generation” models for stand-alone climate components (e.g., atmosphere, land-ice, sea-ice, ocean, land, biogeochemistry), as well as talks addressing the challenges in coupling climate components for integration into ESMs. Of particular interest are:

  1. efficient computational strategies and software for tackling the complex, nonlinear, multi- scale, multi-physics problems arising in climate modeling, with an eye towards next- generation hybrid platforms,
  2. advanced analysis techniques that can inform/enhance existing models through the incorporation of observational data, e.g., approaches for model initialization/calibration, uncertainty quantification and data assimilation, and
  3. emerging work involving the integration and application of data-driven methods, including artificial intelligence (AI) and machine learning (ML), into climate modeling and analysis.

Smart Applications of Scientific Computing


Nowadays there is a wide variety of mathematical software available: computer algebra systems, technical computing languages, automated deduction systems, dynamic geometry systems, ... This minisymposium is devoted to practical real-world applications of this software in fields like: transportation engineering, electrical engineering, big data, machine learning, medicine, biology, knowledge based systems, smart cities, accelerated time simulations, models of queuing systems, ... (this is not an exhaustive list). The focus will be on advanced and smart applications with a nontrivial mathematical background.

Particle based simulations for industrial problems


This mini-symposium explores the impact that simulations of particulate systems are playing in shaping a new paradigm for design engineering. Simulating problems at an industrial-scale using particle simulations (aka DEM/DPM) is extremely challenging, due to large particle numbers and complex multi-physics at the micro scale.

Thus, particle simulations have seen limited uptake compared to other CAE tools such as CFD, FEM. However, steps towards industrially useful simulations have been made by developing novel algorithms and/or parallel computing implementations along with micro scale contact models of complex physics phenomena. Due to the complex nature of these simulations, both industry and academic and developing/using open-source codes, as it allows faster and cheaper development. This mini-symposium is open to both particle simulations and particle based methods for solving continuum equations e.g. smoothed particle hydrodynamics and lattice Boltzmann method. It will focus on algorithms and computational implementations that accelerate particle based methods as well as applications to industrial problems and open-source implementations.

PDE Eigenvalue Problems: Computational Modeling and Numerical Analysis



  • Sebastián Andrés Domínguez-Rivera
  • Patrick Henning
  • Xuefeng Liu
  • Nilima Nigam
  • Daniel Peterseim
  • Jiguang Sun
  • Lambert Theisen
  • Tomáš Vejchodský

Spectral analysis of differential operators provides important insight into the behaviour of physical systems and is often essential in the design and optimization of such systems. Its central role in areas such as structural mechanics and quantum mechanics is well-established. Additionally, an appropriately chosen collection of eigenvectors is often very effective in significantly reducing the computational effort necessary to analyse complex systems. As such, the design and analysis of algorithms for computing eigenvalues and eigenvectors, as well as the extension to new applications, continue to be active and relevant areas of research, with significant room for further development.

The aim of this minisymposium is to present a broad survey of recent work on eigenvalue problems for partial differential equations, considering eigenvalue/vector computations both from the perspective of numerical analysis and in terms of applications for which such computations play an important role. Expected topics of discussion include: eigenvector localization, spectral projection-based method, model order reduction, parameter-dependent eigenvalue problems, nonlinear eigenvalue problems, error analysis, self-adaptive approximation, inexact eigenvalue solvers and novel approximation techniques.

Digital Twins and Parameter Estimation


In contrast to data-driven or physics-based models of generic processes and assets, digital twins rely on sensor data to enable model updating through parameter estimation (physics-based) or model construction (data-driven) that represents a specific process or asset. Various approaches exist to develop digital twins that include data-driven and physics-based generative models that explicitly or implicitly emphasise causal or non-causal models. Digital twins are transdisciplinary in nature that pose various challenges to enable value-adding applications. Contributions focussing on value adding applications or highlighting enablers and challenges of digital twin technology for industrial applications are welcomed, from hardware to inference.

Numerical simulation of ice accretion


In-flight ice accretion can possibly occur if supercooled liquid droplet, ice crystals or snow flakes impact the aircraft. Ice accretion is a major safety hazard to air transportation, and ice shapes can reduce the aerodynamic efficiency, damage aircraft engine or disrupt the operation of probes and control surfaces. Ice accretion impacts on diverse sectors in addition to aviation: wind energy, ground and maritime transportation, civil engineering.

Numerical simulation of ice accretion requires a multidisciplinary approach encompassing aerodynamics, droplet dynamics, liquid film dynamics, water solidification/melting, ice mechanics and shedding, thermal ice protection systems. The goal of the mini-symposium is to provide a snapshot of the state-of-the-art of numerical methods and tools for ice accretion and exemplary application including anti-ice systems, ice accretion on aircraft and wind turbines.