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Conference on Complexity, Future Information Systems and Risk (ins) AS

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Prague

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5th International Conference on Complexity, Future Information Systems and Risk

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UPCOMING DEADLINES

Regular Paper Submission: December 13, 2019

Regular Paper Authors Notification: February 12, 2020

Regular Paper Camera Ready and Registration: February 27, 2020

COMPLEXIS – The International Conference on Complexity, Future Information Systems and Risk, aims at becoming a yearly meeting place for presenting and discussing innovative views on all aspects of Complex Information Systems, in different areas such as Informatics, Telecommunications, Computational Intelligence, Biology, Biomedical Engineering and Social Sciences. Information is pervasive in many areas of human activity – perhaps all – and complexity is a characteristic of current Exabyte-sized, highly connected and hyper dimensional, information systems.

CONFERENCE AREAS

1 . Complexity in Informatics, Automation and Networking

2 . Complexity in Biology and Biomedical Engineering

3 . Complexity in Social Sciences

4 . Complexity in Computational Intelligence and Future Information Systems

5 . Complexity in EDA, Embedded Systems, and Computer Architecture

6 . Network Complexity

7 . Complexity in Risk and Predictive Modeling

CONFERENCE CHAIR

Victor Chang, Xi'an Jiaotong-Liverpool University, China

SCOPE

COMPLEXIS – The International Conference on Complexity, Future Information Systems and Risk, aims at becoming a yearly meeting place for presenting and discussing innovative views on all aspects of Complex Information Systems, in different areas such as Informatics, Telecommunications, Computational Intelligence, Biology, Biomedical Engineering and Social Sciences. Information is pervasive in many areas of human activity – perhaps all – and complexity is a characteristic of current Exabyte-sized, highly connected and hyper dimensional, information systems. COMPLEXIS 2020 is expected to provide an overview of the state of the art as well as upcoming trends, and to promote discussion about the potential of new methodologies, technologies and application areas of complex information systems, in the academic and corporate world.

COMPLEXIS 2020 seeks papers reporting research work, applications or case-studies, on topics indicated below in the section “Conference Areas”. Papers describing advanced prototypes, systems, tools and techniques and general survey papers indicating future directions are also encouraged. Both technological and social-oriented papers are accepted. All papers must describe original work, not previously published or submitted to another conference. Accepted papers, presented at the conference by one of the authors, will be published in the Proceedings of COMPLEXIS under an ISBN, and will be indexed by major indexes. Acceptance will be based on quality, relevance and originality. Both full research reports (regular papers) and work-in-progress reports (position papers) are welcome. There will be both oral and poster sessions.

Special sessions, dedicated to case-studies and focused presentations, as well as tutorials dedicated to technical/scientific topics are also envisaged: companies interested in presenting their products/methodologies or researchers interested in holding a tutorial, workshop or special session are invited to contact the conference secretariat or visit the conference website.

CONFERENCE AREAS

Each of these topic areas is expanded below but the sub-topics list is not exhaustive. Papers may address one or more of the listed sub-topics, although authors should not feel limited by them. Unlisted but related sub-topics are also acceptable, provided they fit in one of the following main topic areas:

1. COMPLEXITY IN INFORMATICS, AUTOMATION AND NETWORKING

2. COMPLEXITY IN BIOLOGY AND BIOMEDICAL ENGINEERING

3. COMPLEXITY IN SOCIAL SCIENCES

4. COMPLEXITY IN COMPUTATIONAL INTELLIGENCE AND FUTURE INFORMATION SYSTEMS

5. COMPLEXITY IN EDA, EMBEDDED SYSTEMS, AND COMPUTER ARCHITECTURE

6. NETWORK COMPLEXITY

7. COMPLEXITY IN RISK AND PREDICTIVE MODELING

AREA 1: COMPLEXITY IN INFORMATICS, AUTOMATION AND NETWORKING

Complexity Theory

Chaos Theory and Applications

Quantum Computing

Information and Entropy

Simulation and Modeling

Automation, Control and Robotics

Connected Vehicles

Complex Networks

Internet and the Semantic Web

Big Data Analytics

Usability of Complex Information Systems

Power Distribution, Energy and Control

AREA 2: COMPLEXITY IN BIOLOGY AND BIOMEDICAL ENGINEERING

Complex Biomedical Systems and Signals

Bioinformatics

Computational Biology

Biological and Biomedical Data Mining

Ontology Engineering

Biomedical Signal Processing

Biomedical Imaging and Data Visualization

Health Systems Complexity

Artificial Life

Population Models

AREA 3: COMPLEXITY IN SOCIAL SCIENCES

Social Networks

Linguistic and Cognitive Systems

Complexity Management

Data-Driven Models

Visualization

Cultural Models

Multi-Agent Systems

Economic Complexity

Information Systems

Security, Privacy and Trust

Gaming

Models of Complex Networks

AREA 4: COMPLEXITY IN COMPUTATIONAL INTELLIGENCE AND FUTURE INFORMATION SYSTEMS

Complex Adaptive Systems

Evolutionary Computing, Neural Computing, Probabilistic Computing

Neuro-Fuzzy Systems, Fuzzy Computing, Logic and Analysis

Self-Organizing Systems, Expert and Intelligent Systems

Deep Learning

Non-Linear Dynamics

Decision Making under Uncertainty

Knowledge-Based Systems

Intelligent Multi-Agent Systems and Intelligent Agents

Climate Change and Natural Science Simulations

Decision Support Systems Services, Tools and Applications

Decision Support Systems Algorithms, Workflows, Processes and Future Advancement

Expert and Intelligent Services, Applications, Proofs-of-Concept and Best Practices

Engineering Design Optimization, Multi-Objective Optimization, Process Optimization

Human-Machine Interfaces, Robotics and Image Processing

Intelligent Information Retrieval, Fusion and Algorithms

Advanced Reasoning, Monitoring and Diagnosis for Systems, Faults and Scientific Discovery

Data/Image, Feature, Decision and Multilevel Fusion

Fusion Theory, Processing, Simulations and Integration

Multi-Sensor, Multi-Fusion System and Application Fusion

Information Fusion Applications in Information/Network Security, Engineering, Health and Finance

Fusion System Design, Algorithm, Computational Resources and Demand Optimization

Information Theory and Applications for Multi-Disciplines

Information Sciences for Implementations, Techniques, Simulations and Proofs-of-Concept

AREA 5: COMPLEXITY IN EDA, EMBEDDED SYSTEMS, AND COMPUTER ARCHITECTURE

System Specification and Modeling

System Design, High-Level Synthesis and Optimization

System Simulation and Validation

Formal Methods and System Verification

Design and Test for Analog and Mixed-Signal Systems and Circuits

Power Modeling, Optimization and Low-Power Design

Temperature and Variability Aware Design and Optimization

Embedded System Design Methodologies

Reconfigurable Computing

Domain and Application-Specific Design

Logical and Physical Analysis and Design

Architectural and Microarchitectural Design

System-on-Chip Design and HW/SW Codesign

Processor, Memory, Storage, Interconnect Designs

Architectures for Instruction-Level, Thread-Level and Memory-Level Parallelism

Large-Scale System Architecture

Compilers and Embedded Systems Software

Performance Evaluation and Measurement of Real Systems

Operating Systems and Middleware

QoS Management and Performance Analysis

New and Emerging Design Technologies

Application Areas, E.G. , Automotive, Avionics, Energy, Health Care, Mobile Devices, Multimedia and Autonomous Systems

AREA 6: NETWORK COMPLEXITY

Community Structure in Networks

Complex Networks and Epidemics

Complex Networks and Mobility

Complex Networks in Biological Systems

Complex Networks in Statistical Mechanics

Complex Networks in Technology

AREA 7: COMPLEXITY IN RISK AND PREDICTIVE MODELING

Time Series Prediction

Big Data Predictive Modeling

Risk Analysis and Management

Risk Minimization, Analytics and Deep Machine Learning

High Performance Computing for Risk

Monte Carlo, Black Scholes, Bayesian, ARIMA, Heston and Stochastic Techniques or Analysis

Error Detection, Reduction and Correction for Risk

Innovative Methods

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