Tracks and Topics

Computational Science and Engineering (CSE) is a relatively new paradigm for scientific research and engineering design in which large-scale simulation, data analysis, and high performance computing play a central role. In fact, the applications of CSE can be seen in almost all disciplines. These include the following:

  • Aerospace Engineering and Mechanical Engineering: combustion simulations, structural dynamics, computational fluid dynamics, computational thermodynamics, computational solid mechanics, vehicle crash simulation, biomechanics, trajectory calculation of satellites
  • Astrophysical systems
  • Battlefield simulations and military gaming, homeland security, emergency response
  • Biology and Medicine: protein folding simulations (and other macromolecules), bioinformatics, genomics, computational neurological modeling, modeling of biological systems (e.g., ecological systems), 3D CT ultrasound, MRI imaging, molecular bionetworks, cancer and seizure control
  • Chemistry: calculating the structures and properties of chemical compounds/molecules and solids, computational chemistry/cheminformatics, molecular mechanics simulations, computational chemical methods in solid state physics, chemical pollution transport
  • Civil Engineering: finite element analysis, structures with random loads, construction engineering, water supply systems, transportation/vehicle modeling
  • Computer Engineering, Electrical Engineering, and Telecommunications: VLSI, computational electromagnetics, semiconductor modeling, simulation of microelectronics, energy infrastructure, RF simulation, networks
  • Epidemiology: influenza spread
  • Environmental Biodiversty, Engineering and Numerical weather prediction: climate research, Computational geophysics (seismic processing), modeling of natural disasters, Spatial Data Prediction: biodiversity management and conservation, role of spatial information, GIS in biodiversity monitoring, geoportals, spatial data infrastructures, global spatial data, spatial tools for natural resources management
  • Finance: derivative pricing, risk management
  • Industrial Engineering: discrete event and Monte-Carlo simulations (for logistics and manufacturing systems for example), queueing networks, mathematical optimization
  • Material Science: glass manufacturing, polymers, and crystals
  • Nuclear Engineering: nuclear blast modeling, fusion simulations
  • Petroleum engineering: petroleum reservoir modeling, oil and gas exploration
  • Physics: Computational particle physics, automatic calculation of particle interaction or decay, plasma modeling, cosmological simulations
  • Transportation

Engineering and science problems have been solved historically using experimental testing and/or mathematical analysis. Some examples of engineering problems are fluid flows and structural properties associated with aircraft, ships, submarines, automobiles, spacecraft, jet and rocket propulsion engines, buildings and other structures. Other examples relate to electrical power generation, weather, rivers and oceans, electrical equipment, computer hardware, radar, antennas, chemical reactions and processes, fuel cells, petroleum recovery and refining, agricultural and construction equipment, refrigeration and air conditioning, air and water pollution, energy conversion and storage, and many others. Many of these problems can now be solved efficiently as computational simulations of mathematical models that represent the relevant physical phenomena arising in each problem.

The Program Committees are looking for original research contributions on a broad-range of topics related to High performance computing, Modeling and simulation, Algorithms, Big Data Analysis and visualization, Data Science, CSE Education, Advanced Networking and Applications and Intelligent and Bio-Inspired Computing. Topics of interest include, but are not limited to the following Research and Application Tracks:

Track 1: High performance computing
High performance computing issues in Big Data analytics   
High performance/large scale application case studies
GPU for general purpose computations (GPGPU)
Multicore and many-core computing
Power aware computing
Cloud, distributed, and grid computing
Asynchronous numerical methods and programming
Hybrid system modeling and simulation
Large scale visualization and data management
Tools and environments for coupling parallel codes
Parallel algorithms and architectures
High performance software tools
Resilience at the simulation level
Component technologies for high performance computing

Track 2: Modeling and simulation
Enterprise Resource Planning
Petri Nets
Virtual Reality and Graphical Simulations
Discrete-Event Simulation
Security/Emergency Support Tools
Plant Simulation
Domain-Specific Tools
Serious Games
Team-support Tools
Education and Training
e-Learning Platforms
Laboratory Simulation Software
Computer Simulation Techniques
Collaborative Systems
Business Process Modeling
Service Value and Supply Chains
Multiscale Simulation
Performance Analysis
Biological and Social Systems Simulation
Agent Based Modeling and Simulation
Biologically Inspired Systems Simulation
Fluid Dynamics
Environmental Modeling
Green Technologies
Crisis and Conflict Management Simulation

Track 3: Numerical and Discrete Algorithms.
Algorithms and data structures
Algorithmic game theory
Algorithmic learning theory
Approximation Algorithms
Combinatorial Algorithms
Combinatorial Optimization
Computational Biology
Computational Complexity
Computational Geometry
Data Structures
Experimental Algorithm Methodologies
Graph Algorithms
Graph Drawing
Parallel and Distributed Algorithms
Parameterized Complexity
Sequential Algorithms
Network Optimization
Online Algorithms
Optimization Algorithms
Randomized Algorithms
Algebraic Combinatorics
Design Theory
Extremal Combinatorics
Graph Theory
Topological and Analytical Techniques in Combinatorics
Probabilistic Combinatorics
Combinatorial Number Theory
Discrete Geometry
Ramsey Theory

Track 4: Big Data Analysis and visualization
Data collection, management and curation
Innovative approaches combining information visualization, visual analytics, and scientific visualization
Streaming methods for analysis, collection and visualization
Novel, extreme or innovative methods for understanding and interacting with data
Advanced hardware for data handling or visualization
Distributed, parallel or multi-threaded approaches
MapReduce-based and database-related methods, algorithms or approaches
Hierarchical data storage, retrieval or rendering
Collaboration or co-design of data analysis with domain scientists
Topics in cognitive issues specific to manipulating and understanding large data
Application case studies
Industry solutions for big data
End-to-end system solutions

Track 5: Data Science
Mathematical, probabilistic and statistical models and theories
Machine learning theories, models and systems
Knowledge discovery theories, models and systems
Manifold and metric learning, deep learning
Scalable analysis and learning
Non-iidness learning
Heterogeneous data/information integration
Data pre-processing, sampling and reduction
High dimensional data, feature selection and feature transformation
Large scale optimization
High performance computing for data analytics
Architecture, management and process for data science
Learning for streaming data
Learning for structured and relational data
Intent and insight learning
Mining multi-source and mixed-source information
Mixed-type and structure data analytics
Cross-media data analytics
Big data visualization, modeling and analytics
Multimedia/stream/text/visual analytics
Relation, coupling, link and graph mining
Personalization analytics and learning
Web/online/social/network mining and learning
Structure/group/community/network mining
Cloud computing and service data analysis
Data warehouses, cloud architectures
Large-scale databases
Information and knowledge retrieval
Web/social/databases query and search
Personalized search and recommendation
Human-machine interaction and interfaces
Crowdsourcing and collective intelligence

Track 6: CSE Education and Finance
Computer Aided Education
Multimedia and Education
Computer Science and Education Technology
Computer and Education Training
Computer and Education Management
Knowledge Discovering

Track 7: Advanced Networking and Applications
Communication Protocol and Architecture
High-speed Communication and Network
Wireless Communication and Network
Mobile Ad-hoc and Sensor Network
Low-power Network and System
Wearable Network and System
Embedded System and Networking
Internet Technology and IP-based Applications
Network Control and Management
Network Performance, Analysis and Evaluation
Quality of Services (QoS)
Ubiquitous/Pervasive Networks and Computing
Ubiquitous Intelligence and Smart World
Smart Object, Space/Environment and System
Innovative Networking and Applications
Social, Ethical & Other Issues of Networked World
Network and Application Hardware

Track 8: Intelligent and Bio-inspired Computing
Artificial Intelligence and Machine Learning
Knowledge Representation and Reasoning
Multi-Agent Systems
Computational Neuroscience
Natural Language Processing
Evolutionary Computation
Memetic Algorithms
Cellular Automata
Fuzzy Systems
Molecular Computing
Applications of Intelligent Computing

Track 9: Applications of CSE
Aerospace Engineering
Astrophysical systems
Biology and Medicine
Civil Engineering
Computer Engineering
Electrical Engineering and Telecommunications
Environmental Biodiversty, Engineering and Numerical weather prediction
Industrial Engineering
Material Science
Mechanical Engineering
Military Battlefield
Nuclear Engineering
Petroleum engineering