Tutorial on Anomaly Detection and Prediction

By | 2009/08/28

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).

Tutorial Format

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

Cost:  $50

To Register, please visit: Tutorial Registration