Conferences  >  Mathematics  >  Modeling and Simulation

Calculus, Differential Equations and Integration,    Computational Physics and Numerical Simulation

Explore how logical formalisms can be used to model diverse phenomena spanning from social sciences to natural languages.

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

Drug design and development are costly and lengthy. Mathematical and computational modelling anchored in model-informed drug development (MIDD) and quantitative systems pharmacology (QSP) methodologies are integral to accelerating the R&D pipeline. In parallel, MIDD and QSP can be used to better understand the biological basis of drug responses and fuel new biomedical research paths. This workshop will bring together experts in the fields of MIDD and QSP with the goal of strengthening ties between industrial and academic researchers and advancing these exciting fields.

Pharmacology and Drug Development,    Applied Mathematics (in general)

The complexity of the problems crucial for understanding the technical, social and, more broadly, systemic challenges related to today's reality, requires the creation and application of appropriate mathematical models and their optimization. Today's world is flooded with an unimaginable amount of data, the usefulness of which depends on the way they are incorporated into mathematical models, which make it possible to explain the nature of the processes and, what is particularly important, to forecast of the future.

Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy

The Energy Modelling Platform – Joint Global Training School 2024 (EMP-G) will be held from 12th to 23rd August. Hosted by the International Centre for Theoretical Physics (ICTP), this is a fantastic opportunity to get free training, access to discussion forums, and coaching skills in models and tools for all of your energy planning needs. Before the beginning of the event on 12th August, there will be a one-week advance tool training, from 5th to the 9th of August.

Courses and Events for Physics Students,    Scientific Computing and Data Science

Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy

Scientific Computing and Data Science,    Ecosystems, Environment and Sustainable Development

University of Waterloo, Canada

The MCQMC conference series is a biennial meeting focused on Monte Carlo (MC) and quasi-Monte Carlo (QMC) methods in scientific computing. The conference attracts between 150 and 200 participants. Its aim is to provide a forum where leading researchers and users can exchange information on the latest theoretical developments and important applications of these methods. Recent conferences have attracted researchers in Markov chain Monte Carlo (MCMC). In a nutshell, MC methods study complex systems by simulations fed by computer-generated pseudorandom numbers. QMC methods replace these random numbers by more evenly distributed (carefully selected) numbers to improve their effectiveness. A large variety of special techniques are developed and used to make these methods more effective in terms of speed and accuracy. The conference focuses primarily on the mathematical study of these techniques, their implementation and adaptation for concrete applications, and their empirical assessment.

Probability and Statistics, Game Theory,    Scientific Computing and Data Science

Fields Institute

This workshop aims to showcase the state-of-the-art mathematical and computational models that are in use in mathematical oncology, with a particular focus on the fourteen hallmarks of cancer. New modeling challenges arise from these hallmarks. Some of the hallmarks relate to the characteristics of the cancer cells themselves (sub-cellular and cellular level), while others include more global effects such as blood circulation, the immune response, the effect and role of the microenvironment, mechanical forces, and the microbiome. Matching the biological diversity of the cancer hallmarks, is the diversity of mathematical approaches and techniques that have been used and are in use to give insight into the growth and spread of cancer – for example, continuum and discrete models; ordinary and partial differential equation models; individual-based and agent-based models; hybrid models; deterministic and stochastic approaches; analytical and computational approaches. Many of these processes act on very different spatial and temporal scales. Hence a new integrated multiscale mathematical modeling framework is needed to include new aspects and insights, such as spatial stochastic models and local and non-local partial differential equation models.

Oncology,    Systems Biology and Computational Biology

University of Vienna, Department of Astrophysics

The BRITE Side of Stars hybride conference will commemorate the ten successful years of BRITE-Constellation. Focus will be on science highlights of BRITE and similar space missions, follow-up projects in stellar astrophysics, data archives, and lessons learned for the next generation - researchers as well as technicians. It will be held in Vienna from August 20 to 23, 2024, and registration will allow you to propose topics which you want to be addressed.

Email: stars24.astro@univie.ac.at

Fields Institute

This workshop aims to take a closer look at how mathematical and computational models can help answer clinically relevant questions and enhance multimodal treatments. Currently, a wide range of modelling approaches study cancer and have a crucial role in treatment delivery from answering questions related to cancer biology and treatment efficacy to directly helping with treatment delivery. In this workshop, we would like to bring together clinicians, biomedical experts, experimentalists, and mathematicians to explore some of the relevant questions on multimodal treatment modelling, efficacy, optimization, drug resistance and clinical delivery.

Oncology,    Systems Biology and Computational Biology

Isaac Newton Institute for Mathematical Sciences

Fields Institute

This workshop explores research in methods aimed at connecting mathematical models of cancer evolution and clinical data. It focuses on ecology and evolution of cancer. Traditionally, ecology and evolution have been the most “mathematical” (and perhaps the first mathematical) areas of biology. Mathematical contributions to these fields made in the 20th century are now fundamental parts of scientific knowledge. More recently, methods of ecology and evolution have found their way into oncology, bridging traditional molecular biology and mathematics including stochastic processes, dynamical systems, and nonlinear partial differential equations. New biological challenges lead to difficult mathematical problems and beautiful solutions, which are both innovative mathematically and impactful from the point of view of public health. These will be the focus of the proposed workshop .

Oncology,    Systems Biology and Computational Biology

Fields Institute

Immunotherapies have revolutionized treatments for several types of cancers, but have been met with clinical trial failures in others. The idea of eliciting an immune response against a tumour is old, but we are only just beginning to harness the potential of the immune system to treat both solid and liquid tumours. To improve immunotherapeutic approaches requires understanding how the immune system interacts around and within a tumour, allowing us to establish effective immunotherapeutic protocols. Mathematical modelling can help identify the mechanisms at the heart of immunotherapeutic efficacy and design successful therapeutic regimens. Close collaboration between experimentalists, clinicians, and quantitative researchers in academia and industry is required to forward models for implementation. This workshop will focus on tightening the links between researchers in different fields to fuel immunotherapy success.

Oncology,    Systems Biology and Computational Biology

Institute for Advanced Study in Mathematics (IASM)

Free boundaries and moving interfaces are ubiquitous in our daily activities such as pouring red wine into a glass, jumping into a swimming pool, or watching water waves at the beach. Other processes involving interfaces are much less visible, but have great impacts on our lives. For example, one mechanism by which cancel cells move around is to change the shape of their boundaries. As another example, three major components in our blood are the red cells, the white cells, and platelets; injure of blood vessels will trigger complicated chemical reactions and physical processes that occur on the interface of these cells. It is therefore extremely important to solve key problems in this scientific field so that we can save money, energy, time, and even human lives. One major tool for sciences in this field is through mathematical modeling and numerical computations. This workshop aims to bring together experts from various disciplines to work together on the analysis, modeling, computation, and applications of a wide range of free-boundary and moving-interface problems.

Numerical Analysis and Computational Mathematics,    Analysis

CIRM – Centre International de Rencontres Mathématiques

Joint Research Center for Advanced and Fundamental Mathematics for Industry

Neural Networks and Artificial Intelligence, Machine Learning,    Implementation and Applications of Artificial Intelligence

Central University of Punjab, Department of Mathematics and Statistics

The FIAM conference, organized by the Forum for Industrial and Applied Mathematics, serves as a premier platform for academia, researchers, and professionals to exchange insights and innovations in the field of mathematical sciences. Through national and international gatherings, FIAM fosters collaboration, showcasing advancements in data analysis, numerical methods, and simulation techniques. With a focus on real-world problem-solving, the conference bridges theory and practice, facilitating dialogue between academia and industry. By uniting diverse perspectives and expertise, FIAM conferences propel research forward, driving solutions to complex industrial challenges and advancing the frontiers of applied mathematics.

Convener;     Phone: [+91-89686-44973];     Email: fiam.conf@cup.edu.in

Artificial Intelligence, Bio-Mathematics, Bio-Statistics, Boolean Functions and their Generalizations, Computational and Theoretical Fluid Dynamics, Computational Mechanics, Control and System Theory Cosmology and Celestial Mechanics, Cryptography, Differential Equations and Applications, Discrete Mathematics, Dynamical Systems and Nonlinear Analysis, Fractional Differential Equations, Fuzzy Systems, Geometry and Topology, Image and Signal Processing, Integral Equations, Mathematical Physics, Modelling and Simulation, Multimedia Security, Nano Fluid Mechanics, Neural Networks, Numerical Techniques, Operations Research, Probability and Statistics, Soft Computing, Soliton Solutions, Wavelet Analysis.

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

Technical Committee on Physical Modelling (TC104) of the International Society of Soil Mechanics and Geotechnical Engineering (ISSMGE)

New facilities, new equipment, and measuring techniques; Resilient Geotechnical Infrastructure; Sustainability in Geotechnical Systems; Energy geo-structures and foundation systems; Application of Machine Learning/Artificial Intelligence in Geotechnical Engineering

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

Scientific-Technical Union of Mechanical Engineering

The study of the processes in different real systems is limited to their modelling, i.e. their approximate description by creating models of these systems and processes. Systems and processes models are divided into two classes - physical and mathematical. In recent decades, it has become clear that the notion of mathematical modelling refers equally to systems of another nature - social, economic, and others. In other words, the behavior of different systems can be effectively explored using their mathematical models. It is only necessary to properly choose the appropriate mathematical apparatus. On the other hand, the range of mathematical models is extremely wide - from algebra and logic to functional analysis. This means that the regular direct contacts between engineer researchers and specialists from different fields of mathematics are very important for the advancement of science and technology. For professional mathematicians, these contacts will enable them to better target the needs of representatives of other areas of knowledge. And the more contacts there are the better. One of the most interesting problems of modern science is the development of methods and models for research and optimization of different systems. Thus knowledge is presented in a form that can be used. More and more mathematics is becoming the language of innovation and intelligent technologies and the modern industrial society.

Scientific-Technical Union of Mechanical Engineering;     Phone: [(+359 2) 987 72 90];     Email: office@mathmodel.eu

Basic principles of mathematical modelling, Analogy principle, Model hierarchy, Methodology of mathematical modelling, System analysis, Mathematical modelling in fundamental and applied physics, mechanics, chemistry and biology, Technological processes as objects of automation, Mathematical methods of management, Modelling of smart production technologies and systems, Virtual technologies and simulations, Information and computer technologies, Robotics, Artificial intellect, Radio electronics, Statistical and stochastic models, Neural networks, Situation modelling,

Mathematical Logic and Foundations,    Neural Networks and Artificial Intelligence, Machine Learning

Institute for Computational and Experimental Research in Mathematics (ICERM)

This workshop showcases emerging frontiers in ROM (reduced order modeling) by bringing together researchers whose core interests lie in model reduction and approximation theory, but who have also explored and developed novel methods that utilize various aspects of statistical learning and data science. Topics of the workshop will include: 1) new mathematical and computational nonlinear ROM formulations required for prediction of transport phenomena, 2) new model reduction and meta-learning opportunities necessitated by the prevalence of large neural network models, 3) new paradigms for ROM capable of attacking parameter inference and ill-posed inverse problems, 4) new frontiers in the automated learning of latent representations due to the availability of computationally feasible optimization in statistical and machine learning, 5) an appropriate computational balancing of observational or experimental data with simulation-based models and ROM that would lead to the usage of ROM in digital twin-scale applications, and 6) challenges and new developments in ROM that aims to preserve inherent physical structure of the underlying dynamics.

ICERM;     Email: info@icerm.brown.edu

reduced order modeling, acceleration, simulation, approximation theory

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