ICCLA 2011 - International Conference on Computational Learning for Aerospace 2011

ICCLA 2011 is to be held at the ultra modern city of Singapore on Jan 10-13, 2011. Best known for its peace and order, besides being the host of many iconic tourism attractions, Singapore has been a favorite venue for holding international conferences and seminars. The conference will address development of novel computational learning techniques for the analysis/application in aerospace and related industries. The goal is to identify prominent areas within the domain of aerospace where developments in computational learning can improve on current techniques and/or answer new interesting questions. The conference will bring together researchers from machine learning, data mining, optimization, and other computational learning topics, as well as researchers and engineers from industry to discuss problems in aerospace. The objective of this conference is three-fold:

To hold tutorials for the benefit of researchers/practitioners from Industry and various disciplines.
To create interdisciplinary discussion and provide feedback on potential solutions.
To stimulate researchers to apply their computational methodologies to the presented problems and to encourage continuous research into similar problems from the field.

Important Dates:
Paper Submission: Aug 1, 2010 Aug 23, 2010
Decision Notification: Sept 1, 2010 Sep 23, 2010
Camera-ready Submission/ Registration: Sept 15, 2010 Oct 07, 2010
Tutorial Proposal: Sep 1, 2010
Prospective authors are cordially invited to submit high-quality papers to ICCLA 2011. The con- ference topics include, but not limited to:

Methodologies:
Intelligent Agents
Bayesian and Generative Modeling
Reinforcement Learning
Kernel Methods
Support Vector Machines
Evolutionary Computing
Memetic Computing
Swarm Intelligent
Neural Networks
Boosting
Multi-view/Multi-task Learning
Probabilistic Methods
Numerical Optimization Methods
Diagnostic and FaultIsolation
Decision-making Under Uncertainty
Validation, Verification, and Metrics
Supervised and Unsupervised Learning
Real-time Machine Learning
Response Surface Modeling


Applications:
Diagnostics and Prognostics of Aircraft Systems
Surface Reconstruction
Anomaly Detection from Aerospace Vehicle Data
Physics-of-failure Modeling
Classification in Large Sky Surveys
Text Mining in Aerospace Information Systems
Privacy and Security Issues in Aerospace Data
Robotic Telescopes
Supervised and Unsupervised Learning in Astro- physics
Predictive Maintenance
Aircraft Safety
Adaptive Robotic Finishing
Combustion Instability
Radar
Sensor Network
Adaptive Monitoring of Aerospace Systems
Prognostic Health Management
Risk Management in Space Missions
MRO Logistics, Strategy, and Regulatory
Paper Submission: Manuscripts should be prepared according to the Springer format and be restricted to a maximum of 12 pages for full paper or 6 pages for poster. Please submit through https://cmt.research.microsoft.com/ICCLA2011.