Thematic tracks organized by experts in particular areas constitute a fundamental part of the conference.
The list of accepted tracks is below. Please click through for a each track’s scope, dedicated web address, and track chair contact details.
We will be adding several more tracks in the coming weeks.
If you are interested in organizing a thematic track at ICCS 2024, you can find all necessary details on the Call for Tracks webpage.
- Computational Health – CompHealth
- Computational Optimization, Modelling and Simulation – COMS
- Multiscale Modelling and Simulation – MMS
- Simulations of Flow and Transport: Modeling, Algorithms and Computation – SOFTMAC
- Smart Systems: Bringing Together Computer Vision, Sensor Networks and Artificial Intelligence – SmartSys
Computational Health – CompHealth
Contact: Sergey Kovalchuk
, Independent Researcher, Russian Federation, email
The field of computational science application in healthcare and medicine (H&M) is rapidly growing. Modeling and simulation, data and process mining, numerical methods, intelligent technologies provide new insights, support decision making, policy elaboration, etc. Moreover, this area gives quantitative support to emerging concepts in the area like P4-medicine (personalized, predictive, preventive, and participatory), value-based healthcare, and others. This thematic track is aimed to bring together research in computational science and intelligent technologies applied in H&M in all the diversity of scales and aspects. Key topics include (but not limited to):
- Simulation and modeling in healthcare and medicine (H&M)
- Complex processes and systems in H&M
- Networks in H&M
- Uncertainty management in H&M
- Numerical methods in H&M
- Data & process mining, ML & AI in H&M
- Knowledge and data processing in H&M
- Decision support and recommending systems in H&M
- Advanced medical information systems
Computational Optimization, Modelling and Simulation – COMS
Contact: Xin-She Yang
, Middlesex University London, United Kingdom, email
The 15th workshop “Computational Optimization, Modelling and Simulation (COMS 2024)” will be a part of the International Conference on Computational Science (ICCS 2024). This will be the 15th event of the COMS workshop series with the first held during ICCS 2010 in Amsterdam, then within ICCS in Singapore, USA, Spain, Australia, Iceland, USA, Switzerland, China, Portugal, Netherlands, Poland, UK and Czech. COMS 2024 intends to provide a forum and foster discussion on the cross-disciplinary research and development in computational optimization, computer modelling and simulation. Accepted papers will be published in Springer’s LNCS Series.
COMS2024 will focus on new algorithms and methods, new trends, and latest developments in computational optimization, modelling and simulation as well as applications in science, engineering and industry.
Topics include (but not limited to):
- Computational optimization, engineering optimization and design
- Bio-inspired computing and algorithms
- Metaheuristics (ant and bee algorithms, cuckoo search, firefly algorithm, genetic algorithms, PSO, simulated annealing etc)
- Simulation-driven design and optimization of computationally expensive objectives
- Surrogate- and knowledge-based optimization algorithms
- Scheduling and network optimization
- Integrated approach to optimization and simulation
- Multiobjective optimization
- New optimization algorithms, modelling techniques related to optimization
- Design of experiments
- Application case studies in engineering and industry
Multiscale Modelling and Simulation – MMS
Contact: Derek Groen
, Brunel University London, United Kingdom, email
Description: Modelling and simulation of multiscale systems constitutes a grand challenge in computational science, and is widely applied in fields ranging from the physical sciences and engineering to the life science and the socio-economic domain. Most of the real-life systems encompass interactions within and between a wide range of spatio-temporal scales, and/or on many separate levels of organization. They require the development of sophisticated models and computational techniques to accurately simulate the diversity and complexity of multiscale problems, and to effectively capture the wide range of relevant phenomena within these simulations. Additionally, these multiscale models frequently need large scale computing capabilities as well as dedicated software and services that enable the exploitation of existing and evolving computational ecosystems.
This MMS track aims to provide a forum for multiscale application modellers, framework developers and experts from the distributed infrastructure communities to identify and discuss challenges in, and possible solutions for, modelling and simulating multiscale systems, as well as their execution on advanced computational resources and their validation against experimental data.
Simulations of Flow and Transport: Modeling, Algorithms and Computation – SOFTMAC
Contact: Shuyu Sun
, King Abdullah University of Science and Technology (KAUST), Saudi Arabia, email
Modeling of flow and transport is an essential component of many scientific and engineering applications, with increased interests in recent years. Application areas vary widely, and include groundwater contamination, carbon sequestration, air pollution, petroleum exploration and recovery, weather prediction, drug delivery, material design, chemical separation processes, biological processes, and many others. However, accurate mathematical and numerical simulation of flow and transport remains a challenging topic from many aspects of physical modeling, numerical analysis and scientific computation. Mathematical models are usually expressed via nonlinear systems of partial differential equations, with possibly rough and discontinuous coefficients, whose solutions are often singular and discontinuous. An important step of a numerical solution procedure is to apply advanced discretization methods (e.g. finite elements, finite volumes, and finite differences) to the governing equations. Local mass conservation and compatibility of numerical schemes are often necessary to obtain physical meaningful solutions. Another important solution step is the design of fast and accurate solvers for the large-scale linear and nonlinear algebraic equation systems that result from discretization. Solution techniques of interest include multiscale algorithms, mesh adaptation, parallel algorithms and implementation, efficient splitting or decomposition schemes, and others.
The international workshop on “Simulations of Flow and Transport: Modeling, Algorithms and Computation” (SOFTMAC) has been held 12 years since 2011 within the International Conference on Computational Science (ICCS). The aim of this symposium is to bring together researchers in the aforementioned field to highlight the current developments both in theory and methods, to exchange the latest research ideas, and to promote further collaborations in the community. We invite original research articles describing the recent advances in mathematical modeling, computer simulation, numerical analysis, and other computational aspects of flow and transport phenomena of flow and transport.
Potential topics include, but are not limited to:
- advanced numerical methods for the simulation of subsurface and surface flow and transport, and associated aspects such as discretization, gridding, upscaling, multiscale algorithms, optimization, data assimilation, uncertainty assessment, and high performance parallel and grid computing;
- spatial discretization schemes based on advanced finite element, finite volume, and finite different methods; schemes that preserve local mass conservation (such as mixed finite element methods and discontinuous Galerkin methods) are of particular interest;
- decomposition methods for improved efficiency and accuracy in treating flow and transport problems; decomposition methods for nonlinear differential equations and dynamical systems arising in flow and transport; temporal discretization schemes for flow and transport;
- a-priori and a-posteriori error estimates in discretizations and decompositions; numerical convergence study; adaptive algorithms and implementation;
- modeling and simulation of single-phase and multi-phase flow in porous media or in free space, and its applications to earth sciences and engineering;
- modeling and simulation of subsurface and surface transport and geochemistry, and its application to environmental sciences and engineering;
- computational thermodynamics of fluids, especially hydrocarbon and other oil reservoir fluids, and its interaction with flow and transport;
- computational modeling of flow and transport in other fields, such as geological flow/transport in crust and mantle, material flow in supply chain networks, separation processes in chemical engineering, information flow, biotransport, and intracellular protein trafficking, will also be considered.
Smart Systems: Bringing Together Computer Vision, Sensor Networks and Artificial Intelligence – SmartSys
Contact: Pedro J S Cardoso
, University of Algarve & LARSyS, Portugal, email
Description: Smart Systems incorporate sensing, actuation, and intelligent control in order to analyze, describe or resolve situations, making decisions based on the available data in a predictive or adaptive manner. Appropriated for computer scientists, mathematicians, as well as researchers from many application areas, pioneering computational methods in distinct research fields, such as space, physics, chemistry, life sciences, economics, security, engineering, arts, humanitarian etc., SmartSys’24 thematic track brings together computer vision, sensor networks, artificial intelligence, data science, applications etc. to solve computational science problems. But other related areas are also welcome, such as in augmented reality, human computer interaction, user experience, Internet of Things/everything, energy management systems & smart grids, vehicles & person tracking and management systems, operational research, evolutionary computation, time-series, and information systems in general, always with the focus in smart systems as modeling, simulation and optimization tools to solve daily computational science-based problems.