Sudipta Kolay

Title: Sudipta Kolay: Innovator in Anomaly Detection Technology

Introduction

Sudipta Kolay is a notable inventor based in East Providence, RI (US). She has made significant contributions to the field of anomaly detection through her innovative patent. Her work focuses on enhancing the accuracy and efficiency of identifying anomalies in various datasets.

Latest Patents

Sudipta Kolay holds a patent titled "Anomaly detection using RPCA and ICA." This invention involves a computing device that identifies anomalies among a plurality of observation vectors. The process begins with projecting an observation vector using a predefined orthogonal complement matrix, which is determined from a decomposition of a low-rank matrix. The low-rank matrix is computed using a robust principal component analysis algorithm. Subsequently, the projected observation vector is multiplied by a predefined demixing matrix to define a demixed observation vector. This demixing matrix is computed using an independent component analysis algorithm along with the predefined orthogonal complement matrix. Finally, a detection statistic value is computed from the defined demixed observation vector. If this value meets or exceeds a predefined anomaly threshold, an indicator is output, signaling that the observation vector is indeed an anomaly. Sudipta Kolay has 1 patent to her name.

Career Highlights

Sudipta Kolay is currently employed at SAS Institute Inc., where she continues to develop innovative solutions in data analysis and anomaly detection. Her expertise in robust principal component analysis and independent component analysis has positioned her as a valuable asset in her field.

Collaborations

Throughout her career, Sudipta has collaborated with talented individuals such as Steven Guanxing Xu and Kai Shen. These collaborations have further enriched her work and contributed to advancements in anomaly detection technologies.

Conclusion

Sudipta Kolay's contributions to anomaly detection through her innovative patent demonstrate her commitment to advancing technology in this critical area. Her work not only enhances data analysis but also provides essential tools for identifying anomalies effectively.