Knoxville, TN, United States of America

Amal Shehan Perera


Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 5(Granted Patents)


Company Filing History:


Years Active: 2010

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1 patent (USPTO):Explore Patents

Title: Amal Shehan Perera: Innovator in Data Mining Technologies

Introduction

Amal Shehan Perera is a prominent inventor based in Knoxville, TN (US). She has made significant contributions to the field of data mining, particularly in the analysis of large spatial datasets. Her innovative approach has led to the development of a unique method that enhances the efficiency and scalability of cluster analysis.

Latest Patents

Amal holds a patent for a "Method and system for data mining of very large spatial datasets using vertical set inner products." This invention presents a system and method for performing and accelerating cluster analysis of large data sets. The data set is formatted into binary bit Sequential (bSQ) format and structured into a Peano Count tree (P-tree) format, which represents a lossless tree representation of the original data. A P-tree algebra is defined and used to formulate a vertical set inner product (VSIP) technique that efficiently measures the mean value and total variation of a set about a fixed point in the large dataset. The VSIPs are instrumental in determining the closeness of a point to a set of points, making them valuable for classification, clustering, and outlier detection.

Career Highlights

Amal is associated with the NDSU Research Foundation, where she applies her expertise in data mining and analysis. Her work focuses on enhancing the capabilities of data processing and analysis, contributing to advancements in various applications.

Collaborations

Amal has collaborated with notable colleagues, including William K. Perrizo and Taufik Fuadi Abidin. These partnerships have fostered innovation and have been pivotal in the development of her patented technologies.

Conclusion

Amal Shehan Perera is a trailblazer in the field of data mining, with her innovative methods paving the way for more efficient data analysis. Her contributions are significant in advancing technology and improving data processing capabilities.

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