I’ll be on NASA TV on March 23, 2011 for the Leading Edge TV Show at 11 am ET. You can watch on NASA TV or www.nasa.gov for a streamed broadcast. We will also be doing a NASA Chat later that day.
NASA Chat, Mar 23, 2pm ET
When an airplane flies, hundreds of data streams fly from it every second — pilot reports, incident reports, control positions, instrument positions, warning modes. But there’s so much data, it’s been nearly impossible for airlines to do anything other than look back for the cause of something that’s already happened. Data mining is the art of digging through mountains of data when you don’t know what you’re looking for or what you might find. Popular search engines like Google™ do this every second. NASA is mining terabytes of aviation data to find issues before they become incidents. Ashok Srivastava will talk to us about what computer tools NASA is building to do the digging.
Jeff Hamlett will talk about how Southwest Airlines is already using data mining “gold” to update their flight operations.
- How is NASA figuring out how to find the needle in a haystack when we don’t know what either looks like?
- What’s an “algorithm”? What’s an “anomaly”? What’s a “precursor” and why do data miners use those words all the time?
- What has Southwest changed in its practices thanks to data mining?
- How is our data mining different from Google’s or Amazon’s? How is it the same?
Join the chat on Mar 23, a few minutes before 2 pm ET at:
A tutorial at the International Workshop on Structural Health Monitoring 2009
September 8th, 2009 1pm-5pm
The tutorial will present methods and applications in the area of data mining and machine learning for large-scale systems such as those found in structural health management applications. The purpose of the tutorial is to discuss and disseminate new publicly available data mining algorithms for anomaly detection and prediction in large-scale applications including distributed systems. We will discuss technical hurdles and possible solutions. Specific focus areas include:
- New anomaly detection algorithms that are fast and highly accurate.
- New prediction algorithms appropriate for massive data sets
- Distributed data mining algorithms which are provably correct (they give the same answer whether data is centralized or distributed).
The 4 hour tutorial will be organized as a series of short lectures with adequate time for audience participation. We will provide an overview of the algorithms covered as well as demonstrations of the methods on real-world data sets. The tutorial will feature multiple speakers who are experts in data mining.
Ashok Srivastava, Ph.D., NASA Ames Research Center
Nikunj Oza, Ph.D., NASA Ames Research Center
Santanu Das, Ph.D., UARC, NASA Ames Research Center
Kanishka Bhaduri, Ph.D., MCT Inc, NASA Ames Research Center
To Register, please visit: Tutorial Registration