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July 13-16, 2009
The WORLDCOMP'09
22 joint conferences


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General Information

Last modified 2008-10-22 19:30

    The 2009 International Conference on Artificial Intelligence (ICAI'09) is held simultaneously (ie, same location and dates: July 13-16, 2009, Las Vegas, USA) with a number of other joint conferences as part of WORLDCOMP'09 (The 2009 World Congress in Computer Science, Computer Engineering, and Applied Computing). WORLDCOMP'09 is the largest annual gathering of researchers in computer science, computer engineering and applied computing. Many of the joint conferences in WORLDCOMP are the premier conferences for presentation of advances in their respective fields (for the complete list of joint conferences Click Here).

    The motivation is to assemble a spectrum of affiliated research conferences into a coordinated research meeting held in a common place at a common time. The main goal is to provide a forum for exchange of ideas in a number of research areas that interact. The model used to form these annual conferences facilitates communication among researchers in different fields of computer science, computer engineering and applied computing. Both inward research (core areas of computer science and engineering) and outward research (multi-disciplinary, Inter-disciplinary, and applications) will be covered during the conferences.

    The last set of conferences had research contributions from 82 countries and had attracted over 2,000 participants. It is anticipated to have over 2,500 participants for the 2009 event.

    The event will be composed of research presentations, keynote lectures, invited presentations, tutorials, panel discussions, and poster presentations.

    You are invited to submit a draft paper of about 5-7 pages and/or a proposal to organize a Technical Session/workshop (see the Submission information). All accepted papers will be published in the respective conference proceedings. The names of technical session/workshop organizers/chairs will appear on the cover of the proceedings/books as Associate Editors.

    Topics of interest include, but are not limited to, the following:

      • Brain models / cognitive science
      • Natural language processing
      • Fuzzy logic and soft computing
      • Software tools for AI
      • Expert systems
      • Decision support systems
      • Automated problem solving
      • Knowledge discovery
      • Knowledge representation
      • Knowledge acquisition
      • Knowledge-intensive problem solving techniques
      • Knowledge networks and management
      • Intelligent information systems
      • Intelligent data mining and farming
      • Intelligent web-based business
      • Intelligent agents
      • Intelligent networks
      • Intelligent databases
      • Intelligent user interface
      • AI and evolutionary algorithms
      • Intelligent tutoring systems
      • Reasoning strategies
      • Distributed AI algorithms and techniques
      • Distributed AI systems and architectures
      • Neural networks and applications
      • Heuristic searching methods
      • Languages and programming techniques for AI
      • Constraint-based reasoning and constraint programming
      • Intelligent information fusion
      • Learning and adaptive sensor fusion
      • Search and meta-heuristics
      • Multisensor data fusion using neural and fuzzy techniques
      • Integration of AI with other technologies
      • Evaluation of AI tools
      • Social intelligence (markets and computational societies)
      • Social impact of AI
      • Emerging technologies
      • Applications (including: computer vision, signal processing, military, surveillance, robotics, medicine, pattern recognition, face recognition, finger print recognition, finance and marketing, stock market, education, emerging applications, ...)
      • The 2009 International Workshop on Machine Learning; Models, Technologies and Applications:
            - General Machine Learning Theory
              . Statistical learning theory
              . Unsupervised and Supervised Learning
              . Multivariate analysis
              . Hierarchical learning models
              . Relational learning models
              . Bayesian methods
              . Meta learning
              . Stochastic optimization
              . Simulated annealing
              . Heuristic optimization techniques
              . Neural networks
              . Reinforcement learning
              . Multi-criteria reinforcement learning
              . General Learning models
              . Multiple hypothesis testing
              . Decision making
              . Markov chain Monte Carlo (MCMC) methods
              . Non-parametric methods
              . Graphical models
              . Gaussian graphical models
              . Bayesian networks
              . Particle filter
              . Cross-Entropy method
              . Ant colony optimization
              . Time series prediction
              . Fuzzy logic and learning
              . Inductive learning and applications
              . Grammatical inference

            - General Graph-based Machine Learning Techniques
              . Graph kernel and graph distance methods
              . Graph-based semi-supervised learning
              . Graph clustering
              . Graph learning based on graph transformations
              . Graph learning based on graph grammars
              . Graph learning based on graph matching
              . General theoretical aspects of graph learning
              . Statistical modeling of graphs
              . Information-theoretical approaches to graphs
              . Motif search
              . Network inference
              . General issues in graph and tree mining

            - Machine Learning Applications
              . Aspects of knowledge structures
              . Computational Finance
              . Computational Intelligence
              . Knowledge acquisition and discovery techniques
              . Induction of document grammars
              . Supervised and unsupervised classification of web data
              . General Structure-based approaches in information retrieval, web authoring, information extraction, and web content mining
              . Latent semantic analysis
              . Aspects of natural language processing
              . Intelligent linguistic
              . Aspects of text technology
              . Computational vision
              . Bioinformatics and computational biology
              . Biostatistics
              . High-throughput data analysis
              . Biological network analysis: protein-protein networks, signaling networks, metabolic networks, transcriptional regulatory networks
              . Graph-based models in biostatistics
              . Computational Neuroscience
              . Computational Chemistry
              . Computational Statistics
              . Systems Biology
              . Algebraic Biology
Academic Co-Sponsors

United States Military Academy, Network Science Center


Biomedical Cybernetics Laboratory, HST of Harvard University and MIT, USA


Argonne's Leadership Computing Facility of Argonne National Laboratory

Functional Genomics Laboratory, University of Illinois at Urbana-Champaign, USA
Minnesota Supercomputing Institute, University of Minnesota, USA
Intelligent Data Exploration and Analysis Laboratory, University of Texas at Austin, Austin, Texas, USA
Harvard Statistics Department Genomics & Bioinformatics Laboratory, Harvard University, USA

Texas Advanced Computing Center, The University of Texas at Austin, Texas

Center for the Bioinformatics and Computational Genomics, Georgia Institute of Technology, Atlanta, Georgia, USA

Bioinformatics & Computational Biology Program, George Mason University, Virginia, USA


Institute of Discrete Mathematics and Geometry, Vienna University of Technology, Austria

BioMedical Informatics & Bio-Imaging Laboratory, Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA
Knowledge Management & Intelligent System Center (KMIS) of University of Siegen, Germany

National Institute for Health Research, UK


Hawkeye Radiology Informatics, Department of Radiology, College of Medicine, University of Iowa, Iowa, USA

Institute for Informatics Problems of the Russian Academy of Sciences, Moscow, Russia.
Medical Image HPC & Informatics Lab (MiHi Lab), University of Iowa, Iowa, USA
SECLAB An inter-university research group (University of Naples Federico II, the University of Naples Parthenope, and the Second University of Naples, Italy)
The University of North Dakota, Grand Forks, North Dakota, USA
Intelligent Cyberspace Engineeing Lab., ICEL, Texas A&M; University (Com./Texas)

International Society of Intelligent Biological Medicine


World Academy of Biomedical Sciences and Technologies



Corporate Sponsor



Other Co-Sponsors
European Commission
High Performance Computing for Nanotechnology (HPCNano)

HoIP - Health without Boundaries


Hodges' Health

The International Council on Medical and Care Compunetics

GridToday - enewsletter focused on Grid, SOA, Virtualization, Storage, Networking and Service-Oriented IT


HPCwire - The Leading Source for Global News and Information Covering the Ecosystem of High Productivity Computing

The UK Department for Business, Enterprise & Regulatory Reform
VMW Solutions Ltd.
Scientific Technologies Corporation

Bentham Science Publishers


 


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San Diego, California, USA
Contact: Kaveh Arbtan

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