Registered Workshops

Thematic workshops organized by an expert in a particular area constitute the core of the conference. The list of accepted workshops is below, click through for brief information and workshop web/contact addresses to follow to find full details.

  1. Advances in High-Performance Computational Earth Sciences: Applications and Frameworks
  2. Advances in the Kepler Scientific Workflow System and Its Applications
  3. Agent-based Simulations, Adaptive Algorithms and Solvers
  4. Applications of Matrix Computational Methods in the Analysis of Modern Data
  5. Architecture, Languages, Compilation and Hardware Support for Emerging ManYcore Systems
  6. Big Data Analytics for Agriculture
  7. Biomedical and Bioinformatics Challenges for Computer Science
  8. Bio-Inspired Algorithms for Complex Networks
  9. Bridging the HPC Talent Gap with  Computational Science Research Methods
  10. Computational and Algorithmic Finance
  11. Computational Chemistry and Its Applications
  12. Computational Finance and Business Intelligence
  13. Computational Flow and Transport: Modeling, Simulations and Algorithms
  14. Computational Optimization, Modelling and Simulation
  15. DDDAS-Dynamic Data Driven Applications Systems and Large-Scale-Big-Data & Large-Scale-Big-Computing
  16. Data-Driven Computational Sciences
  17. Environmental Computing Applications
  18. Large Scale Computational Physics
  19. Mathematical Methods and Algorithms for Extreme Scale
  20. Modeling and Simulation of Large-scale Complex Urban Systems
  21. Multiscale Modelling and Simulation
  22. Nonstationary Models of Pattern Recognition and Classifier Combinations
  23. Solving Problems with Uncertainties
  24. Teaching Computational Science
  25. Tools for Program Development and Analysis in Computational Science
  26. Urgent Computing


Advances in High-Performance Computational Earth Sciences: Applications and Frameworks – IHPCES 2016

Contact: K. Nakajima,
Description: High-performance computing is mandatory for simulations of complex physical phenomena on Earth. At the cross-road of rapid developments in several domains, geoscientists now see more necessities than ever for interactions between researchers on numerics, software, and hardware. This workshop thus aims to provide a forum for presentation and discussion of state-of-the-art research in high-performance computational earth sciences, by earth scientists, applied mathematicians, computational and computer scientists. Emphasis will be on novel advanced high-performance computational algorithms, formulations and simulations, as well as the related issues for computational environments and infrastructure.


Advances in the Kepler Scientific Workflow System and Its Applications – Kepler 2016

Contact: J. Wang,
Description: The Kepler Scientific Workflow System ( supports the design, execution, and management of scientific and engineering workflows through dedicated capabilities including provenance management, run management and reporting tools, integration of distributed computation and data management technologies, ability to ingest local and remote scripts, and sensor management and data streaming interfaces. The Kepler software is developed and maintained by the cross-project Kepler collaboration, which is led by a team consisting of several of the key institutions that originated the project. This workshop aims to bring researchers and developers contributing to Kepler together with informaticians and computational scientists using Kepler in order to communicate recent advances in Kepler and facilitate new development and collaborations.


Agent-based Simulations, Adaptive Algorithms and Solvers – ABS-AA-S 2016

Contact: M. Paszynski,
Description: The aim of this workshop is to integrate results of different domains of computer science, computational science and mathematics.We invite papers oriented toward simulations, either hard simulations by means of finite element or finite difference methods, or soft simulations by means of evolutionary computations, particle swarm optimization and other. The workshop is most interested in simulations performed by using agent-oriented systems or by utilizing adaptive algorithms, but simulations performed by other kind of systems are also welcome. Agent-oriented system seems to be the attractive tool useful for numerous domains of applications. Adaptive algorithms allow significant decrease of the computational cost by utilizing computational resources on most important aspect of the problem.This year following the challenges of ICCS 2016 theme “Data through the Computational Lens” we invite submissions using techniques dealing with large simulations, e.g. agents based algorithms dealing with big data, model reduction techniques for large problems, fast solvers for large three dimensional simulations, etc.


Applications of Matrix Computational Methods in the Analysis of Modern Data – AMCMD 2016

Contact: K. Modarresi,
Description:Modern Data has unique characteristics such as, extreme sparsity, high correlation, high dimensionality and massive size. Modern data is very prevalent in all different areas of science such as Medicine, Environment, Finance, Marketing, Vision, Imaging, Text, Web, etc. A major difficulty is that many of the old methods that have been developed for analyzing data during the last decades cannot be applied on modern data. One distinct solution, to overcome this difficulty, is the application of matrix computation and factorization methods such as SVD (singular value decomposition), PCA (principal component analysis), and NMF (non- negative matrix factorization), without which the analysis of modern data is not possible. This workshop covers the application of matrix computational science techniques in dealing with Modern Data.


Architecture, Languages, Compilation and Hardware Support for Emerging ManYcore Systems – ALCHEMY 2016

Contact: L. Cudennec,
Description: Massively parallel processors have entered high performance computing architectures, as well as embedded systems. In this context, developers of parallel applications, including heavy simulations and scientific calculations will undoubtedly have to cope with many-core processors at the early design steps.In the past sessions of the Alchemy workshop, held together with the ICCS meeting, we have presented significant contributions on the design of many-core processors, both in the hardware and the software programming environment sides, as well as some industrial-grade application case studies. In this 2016 session, we seek academic and industrial works that contribute to the design and the programmability of many-core processors.


Big Data Analytics for Agriculture – BigAg 2016

Contact: R. Dutta,
Description:The main goal of this workshop is to bring Big Data Solutions for Agriculture, to identify the key challenges which are faced by the Big Data Analysts trying to solve problems for agriculture communities, discuss potential solutions and identify the opportunities emerging from cross-domain interactions among agriculture experts, hydrologists, dairy experts, aquaculture experts and Big Data Analytics experts. Therefore, we expect to gain from the domain experts an explanation of how they can apply big data analytics, semantic web standards, machine learning techniques, and linked data standards into their scientific research. We believe this workshop will be a unique opportunity to highlight the main theme of ICCS 2016, ““Data through the Computational Lens”.


Biomedical and Bioinformatics Challenges for Computer Science – BBC 2016

Contact: Mario Cannataro,
Description: Emerging technologies in genomics, transcriptomics, metagenomics and other life science areas are generating an increasing amount of complex data and information. Traditionally, bioinformatics has been focused on the design of methods and technologies facilitating the acquisition, storage, organization, archiving, analysis and visualization of biological and medical data. However, recent changes related to the emerging technologies have made the role of computer science (both theoretical and applied aspects) much more critical in all the bioinformatics research directions. Computational biology, on the other hand, has emphasized mathematical and computational techniques facilitating the modelling and simulation of biomedical processes and systems. In recent years the distinction between these two fields has become increasingly blurred. In order to tackle the growing complexity associated with emerging and future life science challenges, bioinformatics and computational biology researchers and developers need to explore, develop and apply novel computational concepts, methods, tools and systems.Together, these topics cover the key bioinformatics and computational biology techniques and technologies encountered in modern life science environments: (1) Advanced computing architectures/infrastructures; (2) Data/information management and integration; (3) Data/information analysis and knowledge discovery; (4) Integration of quantitative/symbolic knowledge into executable biomedical “theories” or models. The aim of this workshop is to bring together computer and life scientists to discuss emerging and future directions in these areas.


Bio-Inspired Algorithms for Complex Networks – BACN 2016

Contact: H. Chi,
Description: This workshop focuses on bio-inspired algorithms to study the problems of the community detection and the vulnerability of complex networks, including but not limited to, social networks, technological networks, information networks, biological networks, etc. Most real-world complex networks are dynamic and evolutional. The importance of complex networks motivates the need to identify and understand appropriate bio-inspired algorithms that account for better solution for those complex networks. Submitted papers should examine bio-inspired algorithms with solving any type of complex networks. Papers related to simulation complex networks and computational topics are also welcome.This workshop aims to provide a forum for complex networks application scientist, framework developers and experts to identify and discuss challenges in, and possible solutions for, solving complex networks problems in real-world via bio-inspired algorithms.


Bridging the HPC Talent Gap with Computational Science Research Methods – BRIDGE’16

Contact: E.S. Alexandrova,
Description: The workshop focuses on tackling the HPC talent Gap, which is similar, according to IDC and our latest studies, in EU, USA, Japan as well as in BRICS and Latin America. On the other hand we observe mathematics led innovation both in EU and USA, with critical demand of Computational Science Research Methods to bridge the above gap. Thus the focus of the workshop is on the overall environment and how the needed research skills for the changing HPC ecosystem can be built into the PG level and professional development. The intention is to provide forum for discussion highlighting not the single instances on lesson level but rather the means to affect change by increasing Computational Science visibility at curricula and degree level.


Computational and Algorithmic Finance

Contact: Andrey Itkin,
Description:This workshop is intended to present the advances in numerical and computational techniques in pricing, hedging and risk management of financial instruments. The topics include (but not limited to)
– Numerical solutions of pricing equations: finite differences, finite elements, and special techniques in one and multiple dimensions.
– Simulation approaches in pricing and risk management: advances in Monte Carlo and quasi- Monte Carlo methodologies; new strategies for market factors simulation.
– Optimization techniques in hedging and risk management.
– Fundamental numerical analysis relevant to finance
– Numerical techniques and tools for Algorithmic and High-Frequency trading
This workshop is intended to present the advances in numerical and computational techniques in pricing, hedging and risk management of financial instruments. The topics include (but not limited to)
– Numerical solutions of pricing equations: finite differences, finite elements, and special techniques in one and multiple dimensions.
– Simulation approaches in pricing and risk management: advances in Monte Carlo and quasi- Monte Carlo methodologies; new strategies for market factors simulation.
– Optimization techniques in hedging and risk management.
– Fundamental numerical analysis relevant to finance
– Numerical techniques and tools for Algorithmic and High-Frequency trading


Computational Chemistry and Its Applications – CCA 2016

Contact: P. Ramasami,
Description: Computational chemistry uses computers in attempts to solve chemical problems. It uses theoretical methods implemented in software for computations. At the outset of the 21st Century, computational chemistry is leading to a wide range of possibilities usually interdisciplinary due to explosive increase in computer power and software capabilities. Computational chemistry is also integrating the chemistry curriculum. This workshop will provide the opportunity for researchers coming from corners of the world to be on a single platform for discussion, exchanging ideas and developing collaborations. This will be the tenth workshop after being successful events in ICCS since 2003.


Computational Finance and Business Intelligence – CFBI 2016

Contact: Y. Shi,
Description: The workshop focus on computational science aspects of asset/derivatives pricing & financial risk management that relate to business intelligence. It will include but not limited to modeling, numeric computation, soft computing, algorithmic and complexity issues in arbitrage, asset pricing, future and option pricing, risk management, credit assessment, interest rate determination, insurance, foreign exchange rate forecasting, online auction, cooperative game theory, general equilibrium, information pricing, network band witch pricing, rational expectation, repeated games, etc.Green Futures, Inc., China has sponsored the workshop for “Green Future Award of Computational Finance and Business Intelligence” since ICCS 2008. An international award committee will select the awardees from the accepted and registered papers. Once a paper is selected, the author(s) are required to attend the workshop when the awards will be presented.


Computational Flow and Transport: Modeling, Simulations and Algorithms – CFT 2016

Contact: S. Sun,
Description: 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 aim of this special issue 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 as well as review 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.


Computational Optimization, Modelling and Simulation – COMS2016

Contact: X.S. Yang,
Description: The 6th workshop on “Computational Optimization, Modelling and Simulation (COMS 2016)” will be the sixth event of the COMS workshop series at ICCS. COMS 2016 continues to provide a current forum and foster discussions on the cross-disciplinary research and development in computational optimization, computer modeling and simulations. COMS2016 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 (bat algorithm, cuckoo search, firefly algorithm, ABC, GA, PSO etc); Simulation-driven design and optimization of computationally expensive objectives; Surrogate- and knowledge-based optimization algorithms; Scheduling and network optimization as well as design of experiments; Integrated approach to optimization and simulation; New optimization algorithms, modelling techniques related to optimization; Application case studies in engineering and industry.


Dynamic Data Driven Applications Systems and Large-Scale-Big-Data & Large-Scale-Big-Computing – DDDAS/InfoSymbioticSystems

Web Address:
Contact: Erik Blasch,
Description: The Dynamic Data-Driven Application Systems (DDDAS) paradigm forms a realizable symbiotic feedback system between application models of natural and engineered systems and application instrumentation. Through the dynamic integration across computing and measurements, DDDAS creates new capabilities for more accurate analysis, prediction, and control in application systems. The DDDAS paradigm, unifying applications, mathematical modeling, and sensors, is now more relevant than ever with the advent of Large-Scale/Big-Data and Big-Computing. Large-Scale-Dynamic-Data (advertised as the next wave of Big Data), includes the integrated range of data from high-end systems and instruments together with the dynamic data arising from ubiquitous sensing and control in engineered, natural, and societal systems. Multitudes of heterogeneous sensor data collections at large-scales pose system challenges of data storage, recall, analysis, and relevancy. In tandem with Large-Scale is Big Computing, which in addition to the high-end (peta- and exa-scale) data includes a new dimension of distributed computing supporting high-end computing to data collections of networked assemblies of sensors and controllers. The workshop invites papers that showcase advances in the DDDAS paradigm that combine real-world applications, contemporary mathematical approaches, and real-time large scale measurements, that focus on computing and software solutions that meet the emerging demands of big-data solutions. Key applications requiring DDDAS high-end computing solutions include distributed wireless platforms, collections of data for situation awareness, and critical infrastructure systems.


Data-Driven Computational Sciences – DDCS 2016

Contact: C.C. Douglas,
Description:In the late 1960’s, simple data assimilation revolutionarily transformed science in fields based on satellite data. Both NASA and NCAR produced stunningly revolutionary applications. The oil and gas industry jumped on this concept in the early to mid 1970’s creating commercial data assimilation pipeline products by multiple vendors that were used in more than 165 countries in short order. This led to intelligent data assimilation being the normal way to operate a reservoir or pipeline networks by the 1990’s by all of the major oil producers. Since the early 2000’s, government grant agencies (e.g., the National Science Foundation) applied this concept to update numerous fields creating astonishing improvemnts in simulations that continue to this day in many application areas.A data-driven computational system is the integration of a simulation with dynamically and intelligently assimilated data, multiscale modeling, computation, and a two way interaction between the model execution and the data acquisition methods (see the DDDAS Scientific Community Web Site, The workshop will present opportunities as well as challenges and approaches in technology needed to enable Data-Driven Computational Science capabilities in applications, relevant algorithms, and software systems. All related areas in Data-Driven Sciences are included in this workshop, including CyberPhysical Systems like HealthKit on iPhones and iPads as well as similar systems developed by Intel, Google, and Microsoft for phones and tablets, Internet of Things (IoT), Cloud of Things (CoT), and Data Intensive Scientific Discovery (DISD).A recent example is a tranformative way of landing airplanes on time and reduce delays and cancellations is a process known as Time Based Flow Systems (TBFS). It spaces planes by space instead of by time. The first of these systems was developed for Heathrow Airport by Lockheed Martin for the British National Air Traffic Services and fully deployed in May, 2015. It has reduced flight cancellations due to wind by exactly 100% and flight delays by approximately 40% during the period of May – August, 2015.


Environmental Computing Applications – State of the Art – ECA 2016

Contact: M. Heikkurinen,
Description:This workshop focuses on advances in environmental computing (using advanced environmental modelling techniques to analyse data sources with a goal of producing actionable knowledge). The submitted papers can be case studies or present new approaches to environmental computing systems, including (but not limited to) multi-model and multi-data frameworks (including metadata approaches), scalability of the systems, socio-economic impact of environmental computing, data and model semantics and visualisation.


Large Scale Computational Physics – LSCP

Contact: E. de Doncker,
Description: The LSCP workshop will focus on symbolic and numerical methods and simulations, algorithms and tools (software and hardware) for developing and running large-scale computations in physical sciences. Special attention will go to parallelism, scalability and high numerical precision. System architectures are also of interest as long as they are supporting physics related calculations, such as: massively parallel systems, GPU, many-integrated-cores, distributed (cluster, grid/cloud) computing, and hybrid systems. Topics will be chosen from areas including: theoretical physics (high energy physics, nuclear physics, astrophysics, cosmology, quantum physics, accelerator physics), plasma physics, condensed matter physics, chemical physics, molecular dynamics, bio-physical system modeling, material science/engineering, nanotechnology, fluid dynamics, complex and turbulent systems, climate modeling.


Mathematical Methods and Algorithms for Extreme Scale – MATH-EX16

Contact: V.N. Alexandrov,
Description: Novel mathematics and mathematical modelling approaches together with scalable scientific algorithms are needed to enable key science applications at extreme-scale. This is especially true as HPC systems continue to scale up in compute node and processor core count. These extreme-scale systems require novel mathematical methods to be developd that lead to scalable scientific algorithms to hide network and memory latency, have very high computation/communication overlap, have minimal communication, have no synchronization points. The workshop seeks strategic and position papers in the above area and to serve as a forum for Computational Scientists to discuss the mathematical and algorithmic challenges and approaches towards exascale and beyond.


Modeling and Simulation of Large-scale Complex Urban Systems – MASCUS 2016

Description: This workshop focuses on modeling and simulation of large-scale urban systems for planning and decision support. Submitted papers should examine urban processes from a complex systems perspective, including (but not limited to) methodologies such as agent-based modelling and complex networks. Application areas can include any form of urban system. For example, this includes transportation, human crowds, water, power, land use, etc. Work which investigates the interactions and interdependencies of different urban processes are of particular interest for this workshop. Papers related to simulation scaling and computational topics are also welcome. For example, this includes high-performance computing, multi-scale modelling, model interoperability and visualization.


Multiscale Modelling and Simulation, 13th International Workshop

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 workshop 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. This workshop is a successor of the series of workshops on Simulation of Multiphysics Multiscale Systems organized during 2002-2015.


Nonstationary Models of Pattern Recognition and Classifier Combinations – NMRPC 20162

Contact: M. Wozniak,
Description: The progress of computer science has caused that many institutions collected huge amount of data, which analysis is impossible by human beings. Nowadays simple methods of data analysis are not sufficient for efficient management of an average enterprise, since for smart decisions the knowledge hidden in data is highly required. The great disadvantage of the aforementioned methods is that they “assume” that statistical properties of the discovered concept (which model is predicted) are being unchanged. In a real situation we could observe the so-called concept drift, therefore designing data mining methods, especially classification ones for data streams is currently the focus of intense research. On the other ha nd, we can usually use a number of classifiers for each of pattern recognition tasks which differ each other. Therefore developing combined classifiers has been mentioned as ones of the most promising trends in the pattern recognition which can exploit unique elementary classifier strengths and could adapt to the changes of classification models.


Solving Problems with Uncertainties – SPU 2016

Contact: V.N. Alexandrov,
Description: Problems with uncertainty need to be tackled in an increasing variety of areas ranging from problems in physics, chemistry, computational biology to decision making in economics and social sciences. Uncertainty is unavoidable in almost all systems analysis, in risk analysis in decision making and economics and financial modeling, in weather and pollution modeling, disaster modeling and simulation, etc. With the advent of exascale computing larger and larger problems have to be tackled in a systematic way and the problem of solving such problems with uncertainties and quantifying the uncertainties becomes even more important due to the variety and scale of uncertainties in such problems. The focus of the workshop will be on methods and algorithms for solving problems with uncertainties, stochastic methods and algorithms for solving problems with uncertainty, methods and algorithms for quantifying uncertainties such as dealing with data input and missing data, sensitivity analysis (local and global), dealing with model inadequacy, model validation and averaging, software fault-tolerance and resilience, etc.


Teaching Computational Science – WTCS 2016

Contact: A.B. Shiflet,
Description: The ninth Workshop on Teaching Computational Science (WTCS) solicits submissions describing innovations in teaching computational science in its various aspects (e.g. modeling and simulation, high-performance and large-data environments) at all levels and in all contexts. Typical topics include innovations in course content or curriculum structure, instructional methods or assessment, teaching or learning tools, alternative approaches, and non-academic training in computational sciences. These innovations may involve introductory programming, service courses, specialist undergraduate or postgraduate topics, industry-related short courses. We welcome submissions directed at issues of current and local importance, as well as topics of international interest.


Tools for Program Development
and Analysis in Computational Science – Tools 2016

Contact: K. Fuerlinger,
Description:The use of supercomputing technology, parallel and distributed processing, and sophisticated algorithms is of major importance for computational scientists. Yet, the scientists’ goals are to solve their challenging scientific problems, not the software engineering tasks associated with it. For that reason, computational science and engineering must be able to rely on dedicated support from program development and analysis tools.The primary intention of this workshop is to bring together developers of tools for scientific computing and their potential users. Paper submissions by both tool developers and users from the scientific and engineering community are encouraged in order to inspire communication between both groups. Tool developers can present to users how their tools support scientists and engineers during program development and analysis. Tool users are invited to report their experiences employing such tools, especially highlighting the benefits and the improvements possible by doing so.


Urgent Computing: Computations for Decision Support in Critical Situations – Urgent Computing (UC 2016)

Contact: A.V. Boukhanovskiy,
Description: Decision support in critical situations comprising complex technical, environmental and social systems is a difficult interdisciplinary research area which is based on data-driven technologies, high-performance simulation and visualization facilities. The computational concept of urgent computing is considering as computational services (or resources) as data services work jointly in distributed environment for the help decision maker to make an optimal behavior scenario in time limitations.
The main topics of the workshop are: Methods and the principles of urgent computing; Urgent computing platforms and infrastructures; Simulation-based decision support for complex systems; Interactive visualization for decision support in emergency situations; Domain-area applications to emergency situations, including natural disasters, transportation problems, epidemics, criminal acts, financial crisis etc.