Conferences  >  Mathematics  >  Modeling and Simulation

Lake Como School of Advanced Studies

Probability and Statistics, Game Theory,    Courses and Events for Math Students and Early Career Researchers

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

Courses and Events for Math Students and Early Career Researchers,    Applied Mathematics (in general)

Technical University of Munich

The second international workshop on Mathematical Modeling and Scientific Computing (MMSC) dedicated to the memory of Nikolai Botkin (22.03.1956-14.09.2019) will be held from October 4th to 7th, 2022, at the Technical University of Munich. Nikolai Botkin made a significant contribution to the creation and mathematical analysis of mathematical models, the development of numerical methods and algorithms for optimal control of ordinary and distributed systems, elasticity theory, hydrodynamics, thermodynamics, and homogenization theory. The first workshop (November 19-20, 2020) was organized by the Technical University of Munich and approved by the DFG. It was held online because of Covid-19 situation.

The objective of the event is to create an interdisciplinary workshop, which brings together international experts working on mathematical models from various fields. These fields include control theory, material science, medicine, and aerospace, to name a few. Despite the different applications of mathematical models, the underlying concepts related to the modelling of complex processes and systems share many common features. The same holds for the application of scientific computing methods for the numerical implementation of the mathematical models. These methods nowadays constitute an integral part of the research task in applied fields. Topics such as parallel computing on high performance computer systems and the use of shared memory architectures are vital e.g. for the solution of partial differential equations arising in various fields. Rapidly developing technologies like machine learning methods became indispensable in data analysis. It is believed that bringing together experts from different fields will lead to new innovative ideas and create synergies between the scientific research topics.

Email: turova@ma.tum.de

Mathematical and computer modeling of physical and biological processes, Optimization, control and numerical methods for ODEs and PDEs, Computer technologies and data analysis in engineering and bioinformatics, High performance scientific computing for physical and biomedical applications

Scientific Computing and Data Science,    Numerical Analysis and Computational Mathematics

Humboldt-Universität zu Berlin

Our goal with ICSB 2022 is to re-ignite the vibrant field of systems biology. We have selected a set of topics and speakers we think can excite you all and we hope you will enjoy our great city and the programme.

Our line-up of keynotes and session chairs/speakers is amazing and we encourage you all to submit talks and posters.

Please join us in making ICSB 2022 the best ICSB ever. We are going all in on trying to reboot the community after the pandemic. This meeting will be in person and full of exciting science!

The Call website can be found here on the EasyChair platform:

https://easychair.org/cfp/ICSB2022

The main conference website is https://www.icsb2022.berlin

Global INBOX;     Email: info@icsb2022.berlin

MULTI-SCALE MODELS, MACHINE LEARNING / ARTIFICIAL INTELLIGENCE, ALPHA FOLD, DEEP HIDDEN PHYSICS, SINGLE CELL MODELING, WHOLE CELL MODELING, TUMOR ECOSYSTEMS, SIGNAL TRANSDUCTION, CANCER SYSTEMS BIOLOGY, COMPUTATIONAL PATHOLOGY, IMAGING ALGORITHMS, NETWORK BIOLOGY & PRECISION MEDICINE, MICROBIOMES, CLIMATE & BIOTOPES, MODELS IN TIME AND SPACE, PLANT SYSTEMS BIOLOGY, INTEGRATION OF COMPUTATIONAL APPROACHES, CLINICAL IMPACT/CHALLENGES FOR SYSTEMS BIOLOGY, PREVENTING FUTURE PANDEMICS, POST PANDEMIC LIFE SCIENCE, YOUNG SCIENTIST FORUM, CAREER TRACK, WILDCARD *.talks

Biology,    Neural Networks and Artificial Intelligence, Machine Learning

CIRM – Centre International de Rencontres Mathématiques

The Institute for Advanced Study in Mathematics (IASM) in Hangzhou, China

La Trobe University, Melbourne

This conference will precede the biennial Forum Mathematics for Industry FMfI2022 to be held at the same location 21-24 November.

Lublin University of Technology

The main objective of the CMES conference is the development of engineering sciences, numerical and experimental techniques, broaden experience, and good practices by representatives of the scientific community and industry. The conference allows the exchange of knowledge between different research domestic and foreign centres representing various fields of engineering science and technology.

Department of Organisation of Enterprise, Faculty of Management, Lublin University of Technology;     Phone: [+48815384410];     Email: contact@cmes.pl

Analysis of engineering processes, Application of computer programs in technology, Artificial and computational intelligence, Computational fluid dynamics (CFD), Computer simulations of processes and phenomena, Finite Element Method (FEM), Material properties and structure research methods, Production engineering and quality control, Technology management in energy acquisition processes.

Engineering (general),    Mechanical engineering

The Fields Institute

One goal of this workshop is to facilitate the exchange of novel ideas and results in mathematical ecology and to showcase the importance of the field in the face of many challenges from invasive species to climate change. Another goal is to celebrate and honour the exceptional achievements in the area of mathematical ecology of Prof Mark Lewis (Alberta) on the occasion of his 60th birthday (December 5, 2022).

The aim is to train undergraduate, post-graduate, early-career and other international junior scientists from the fields of water and the environment, land surface science, water resources, ecology, hydrometeorology, biogeochemistry and other related research areas concerned with the delivery of next-generation land-surface and hydrological predictions. You will learn the technical skills to run JULES and standalone Hydro-JULES tools in order to investigate hydrological processes under current and future scenarios, understand how to use the technical features built in Hydro-JULES for collaboration in scientific projects.

Hydrology,    Computational Physics and Numerical Simulation

Institute for Pure and Applied Mathematics (IPAM)

For molecular systems we know the laws of physics to extreme precision. Yet, our ability to compute properties of these systems to numerical precision is very limited. This is mainly due to two sources of computational intractability: quantum mechanics and chaos. On one side, the accurate solution of the Schrödinger equation for large molecular systems is computationally prohibited. One the other side, even if we knew the forces exactly, the dynamical equations for the atoms would exhibit chaotic behaviour, which implies that, just as the weather, we have limited capacity to predict future trajectories. Some aspects of these systems remain predictable at a macroscopic scale, but they require completely different variables, such as pressure, temperature and entropy. We call this emergent theory thermodynamics.

In the completely different discipline of machine learning, a fairly similar phenomenon takes place. The microscopic variables of an image are given by its constituent pixel values. When we analyse the image with a deep neural network (DNN), we will detect edges in the first layer, corners in the next layer, then the object parts and finally, at the top of the neural network, entire objects. We understand the world at the “emergent” level of objects and their relations, not at the level of pixels and edges. In deep learning (DL) emergence happens automatically through learning and some inductive biases such as symmetries.

A major question we want to address in this workshop is whether we can apply the same learning paradigm to the field of molecular science to learn the correct emergent variables and dynamics.

Applied Mathematics (in general),    Neural Networks and Artificial Intelligence, Machine Learning

The Research Institute for Mathematical Sciences (RIMS)

Thermodynamics, Fluid Dynamics and Statistical Physics,    Applied Mathematics (in general)

CIRM – Centre International de Rencontres Mathématiques

Neural Networks and Artificial Intelligence, Machine Learning,    Genomics and Bioinformatics

CIRM – Centre International de Rencontres Mathématiques

The workshop will bring together both experienced researchers and promising young scientists from different scientific backgrounds, interested in the interplay between theoretical and applied research. It will promote the participation of male and female researchers with a good gender balance among speakers. The conference will place an emphasis on the connections between the areas and on directions for future research. We expect a high-level and high-impact event which will inspire new collaborations and will open new research directions.

Complex Systems, Chaos and Self-Organisation,    Scientific Computing and Data Science

CIRM – Centre International de Rencontres Mathématiques

ICMS - International Centre for Mathematical Sciences

This workshop will focus on developing new statistical solutions to address these new ecological data-driven challenges.

Applied Mathematics (in general),    Probability and Statistics, Game Theory

Imperial College London

The objective of the conference is to provide a forum for exchange of ideas and discussions on topics related to different forms of numerical modelling in geotechnical engineering. Both senior and young researchers, scientists and practitioners from Europe and overseas are warmly invited to attend this conference to share and exchange their knowledge.

Civil Engineering, Architecture, Construction and Geotechnical Engineering,    Geophysics and Geology

This 14th Edition aims to cover traditional topics of MCM conferences (Computational statistical physics, Quasi Monte Carlo methods, Markov Chain Monte Carlo in high dimension, Multilevel methods, Rare events simulation, Stochastic gradient and other stochastic optimization methods�) as well as emerging topics coming from applications and from artificial intelligence as: Generative models, Experimental design in Uncertainty Quantification, Monte Carlo simulations and High Performance computing, Reinforcement learning and control, Statistical learning and Monte Carlo sampling, Economic and industrial applications (Deeptech, finance, medicine, climate risks for instance).

Email: https://mcm2023.sciencesconf.org/

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

In this workshop, we will explore how the research realms of generative modelling and 3D neural representations can benefit from each other, as well as explore novel applications in different areas of science and technology.

Neural Networks and Artificial Intelligence, Machine Learning,    Scientific Computing and Data Science

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Computational Physics and Numerical Simulation,    Mathematical Physics

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

What have we learned from the COVID-19 pandemic, and how can we be better prepared for the next global outbreak? This workshop brings together collaborative teams of modellers, statisticians, epidemiologists, genomics experts, public health decision-makers, and those implementing and delivering interventions who have been working together in a research network, aiming to increase Canada’s capacity for data-driven emerging infectious disease modelling to directly support future public health decisions. This BIRS meeting is an important opportunity for network members and collaborators to share the outcomes of their research over the two years since the network was launched with funding from the federal government. The questions being tackled at this workshop are grounded in public health needs and generated in partnership between research investigators and knowledge users – public health leaders, health administrators and policy-makers.

Epidemiology & Public Health,    Systems Biology and Computational Biology

CIRM – Centre International de Rencontres Mathématiques

Computational Physics and Numerical Simulation,    Scientific Computing and Data Science