Scientific Program
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ISBIS-2010 will provide a varied and stimulating scientific program of invited and contributed papers, and excellent opportunities for formal and informal exchanges.
It will have four main themes:
- Statistical Image Analysis – see below for more details
- Large and Complex Data Sets – see below for more details
- Statistics in Financial Services
- Quality in Health Services
KEYNOTE SESSIONS
The conference will open and close with plenary sessions led by two worlds in their areas.
On Tuesday morning July 6, after the Opening Ceremony, the opening Keynote Address will be presented by Jean Serra, co-founder with George Matheron of the morphological approach to Image Analysis, in which he will review the history and development of the subject. In one of the parallel streams, Jean will provide a tutorial introduction to Image Analysis. The final session will feature case studies presented by Adrian Baddeley, Leanne Bischoff and Luc Vincent.
Jean Serra is, with George Matheron, the co-founder of the morphological approach to Image Analysis that has provided the basis for handling a vast range of problems in optical microscopy, histology, signal compression, multispectral imagery, material sciences and many other industrial settings. Most recently, he has turned his attention to environmental problems. Following his PhD studies at Nancy, he moved to the Paris School of Mines at Fontainebleau, where he subsequently established his own research group in Image Analysis and Mathematical Morphology. He has many writings and inventions to his name, including over 100 papers, 10 books, and several patents. He was founder and first President of the International Society for Mathematical Morphology. He has received numerous awards the ESCLANGON price, awarded by the French Society of Physics the first award of the Grand Prix of the AFCET Society (French equivalent of the IEEE), Chevalier of the National Order of Merit, France, and Doctor Honoris Causa of the Autonomous University of Barcelona.
In 2004, he wrote: "I am fascinated by the process that makes the world intelligible, and which, conversely, goes back from theory to an actual handling of things. That is the reason why I designed and patented image analysers, and why I launched several companies, for industrial control, for fingerprints, for quantitative microscopy, and others."
On Friday afternoon, July 9, there will be a plenary session on the future of statistical analysis for Large and Complex Data Sets, featuring William Cleveland, Suptarshi Guha and John Morrison. Then the closing Keynote Address on the future of statistical computing for massive data sets will be presented by Lee Edlefsen.
Lee Edlefsen is Vice President of Engineering of REvolution Computing, a venture-funded commercial open source company whose objective is to be to "R" what Red Hat has been to Linux. He holds a Ph.D. from Harvard University, and has had a long career developing data analysis and visualization software. He played a leading role in designing and developing three award-winning, commercially successful software programs (Gauss, Axum, and S-PLUS for Windows), and was the co-founder and CEO of three successful software companies.
Lee has had a long-standing interest in high performance computing and especially in the analysis and visualization of large complex data sets. Gauss, developed in the mid-1980's, was built on algorithms that allowed arbitrarily-large data sets, as, later, was Axum. Both won PC Magazine Editor's Choice awards. More recently, he served for several years as a consultant to organizations trying to deal with huge data challenges, and during that time developed ExaStat, an extremely fast interactive data analysis program capable of handling huge data sets and of distributing the computations across multiple computers and multiple cores on each computer. He is currently leading a project at REvolution Computing to add extremely fast, distributed, huge data capabilities to R.
Invited Paper Sessions will include the following topics:
- y-BIS Special Invited Session with the Editors
- Applications of Entropy Optimization Principles in Statistics and Economics
- Challenges in Analyzing Complex Data
- Chemometrics
- Component-based and Probabilistic Modeling of Predictive Paths between Complex and Multiple Datasets
- Computer Experiments
- Data Mining Applications
- Data Quality Mining
- Health and Safety Surveillance
- Image Analysis
- Large and Complex Data Sets
- Medical Image Analysis
- Methodologies for Post-Euclidean Statistics
- Mixture Design
- Object-oriented Data Analysis
- Professional Development for Statisticians
- Quality, Efficiency, Patient Safety and Patient Satisfaction
- Reliability
- Spatial Extreme Value Statistics
- Statistical Process Control
- Statistics and Networks
- Statistics in the Information Sciences
- Statistics: a SWOT analysis
- Time Series and Spectral Modeling
- Topics in Time series analysis
- Transportation
- Warranty Analysis
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