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September 10, 2007
CSE graduate student Amrudin Agovic received the best student paper runner-up at the 1st ACM Workshop on Knowledge Discovery from Sensor Data (Sensor-KDD). The award is for his paper, entitled "Anomaly Detection in Transportation Corridors using Manifold Embedding Methods."
For his paper, Agovic said he used manifold embedding methods for feature preprocessing. He said reducing the dimensionality can reveal the data structure and simplify anomaly detection in some cases. Agovic said he used the domain of secure transportation corridors, set up as part of the SensorNet project. Secure transportation corridors are networks of roads equipped with weigh stations where trucks are required to pass regularly, helping to accumulate a lot of truck data. The objective of the research was to find suspicious trucks and help determine which trucks need to be examined further.
This work was a joint project with the Oak Ridge National Labs. The award included a certificate and $500 prize. For more information about his work, visit Amrudin Agovic's home page.
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