Events Calendar

CS PhD Colloquium: Om Prasad Patri (USC) - Shape Mining for Multisensor Event Recognition

Speaker: Om Prasad Patri, USC

Talk Title: Shape Mining for Multisensor Event Recognition

Series: CS Colloquium

Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.

CS PhD Colloquium Lecture Event.
The ubiquitous rise of sensors in our daily lives, as well in industrial and engineering equipment, have led to emerging challenges in pattern analysis of large amounts of multisensor data to identify critical events automatically. This talk presents our recent work on framing this event recognition problem in the context of time series classification by automatically finding discriminative shapes or patterns (called shapelets) within sensor data. These unconventional shape mining approaches show potential for real-world sensor datasets, such as equipment monitoring data from an oil field or a manufacturing plant, as they don't make assumptions about the nature and structure of the input sensor data and provide visual intuition in the form of the extracted shapes for further analysis by domain experts, instead of being a black-box machine learning approach.

These approaches also perform fast classification as they focus on throwing away most of the data after finding the discriminative shapelets. By combining shape extraction and feature selection, this temporal pattern mining paradigm can be extended for processing data from multiple sensors. This talk describes algorithmic strategies for performing this combination, and presents results and motivational examples from modern industrial systems where our approaches are applicable. An interesting application of the proposed approach using shape mining for identifying malware from Windows portable executable files is also discussed.

Biography: Om P. Patri is a PhD candidate in Computer Science at USC, advised by Prof. Viktor K. Prasanna. His interests are broadly in the areas of data science, AI, cybersecurity and event-based systems, and his dissertation research is on modeling and recognition of events from multisensor time series data. At USC, he has been a part of the Center for Smart Interactive Oil Field Technologies (CiSoft) and the USC Data Science Lab. During his graduate studies at USC, he has worked with NEC Labs America and Cylance Inc. Before coming to USC, he obtained a Bachelors in Computer Science from the Indian Institute of Technology Guwahati.

Host: CS Department

Location: Henry Salvatori Computer Science Center (SAL) - 101

Audiences: Everyone Is Invited

Contact: Assistant to CS chair