Company Filing History:
Years Active: 2021-2022
Title: Sean Michael O'Connor: Innovator in Time-Series Analytics and Defect Detection
Introduction
Sean Michael O'Connor is a notable inventor based in Kenmore, WA (US), recognized for his contributions to technology through his innovative patents. With a total of two patents to his name, O'Connor has made significant strides in the fields of time-series analytics and image-based defect detection.
Latest Patents
O'Connor's latest patents include the "Intelligent Time-Series Analytic Engine" and "Intelligent Defect Detection from Image Data." The Intelligent Time-Series Analytic Engine focuses on processing multiple time-series data sequences to identify anomalies and forecast future trends using advanced machine learning models such as recurrent neural networks (RNN), convolutional neural networks (CNN), and generative adversarial networks (GAN). This invention automates the segmentation of time-series data and provides alerts to users regarding detected anomalies. The Intelligent Defect Detection from Image Data patent involves analyzing images of items to identify defects. It utilizes image augmentation and machine learning-based image synthesis to generate synthetic images, which are then processed to determine defect characteristics and root causes, ultimately generating alerts for remediation.
Career Highlights
Sean Michael O'Connor is currently employed at Accenture Global Solutions Limited, where he applies his expertise in technology and innovation. His work focuses on developing solutions that leverage machine learning and data analytics to improve processes and outcomes in various industries.
Collaborations
O'Connor collaborates with talented professionals such as Tim Wu and Takuya Kudo, contributing to a dynamic work environment that fosters innovation and creativity.
Conclusion
Sean Michael O'Connor's contributions to the fields of time-series analytics and defect detection exemplify the impact of innovative thinking in technology. His patents reflect a commitment to advancing machine learning applications, making significant strides in improving efficiency and accuracy in various processes.