Mountain View, CA, United States of America

Michael Radwin

This inventor holds 1 USPTO granted patent. Top assignee: Intuit, Inc.. Active years: 2019.


% Patents Active = 100.0

Average Co-Inventor Count = 3.0

ph-index = 1

Forward Citations = 14(Granted Patents)


Company Filing History:


Years Active: 2019

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1 patent (USPTO):Explore Patents

Title: Michael Radwin: Innovator in Anomaly Detection

Introduction

Michael Radwin is a notable inventor based in Mountain View, CA (US). He has made significant contributions to the field of data analysis, particularly in detecting anomalous values in small business entity data. His innovative approach has the potential to enhance the accuracy and reliability of financial data assessments.

Latest Patents

Michael Radwin holds 1 patent for his invention titled "Detecting anomalous values in small business entity data." This method involves identifying account data of an entity for a present time period, where the account data includes more than one first data value. The process creates a comparison group that includes second data values originating from a prior time period. By selecting subsets from both the first and second data values, the method identifies anomalous values through comparison, allowing for timely actions to be initiated in response to these anomalies.

Career Highlights

Michael Radwin is currently employed at Intuit, Inc., where he applies his expertise in data analysis and anomaly detection. His work contributes to the development of innovative solutions that assist small businesses in managing their financial data more effectively.

Collaborations

Michael has collaborated with talented individuals such as Saikat Mukherjee and Kevin Michael Furbish. These partnerships have fostered a creative environment that encourages the development of groundbreaking ideas and technologies.

Conclusion

Michael Radwin's contributions to the field of anomaly detection exemplify the impact of innovative thinking in data analysis. His work at Intuit, Inc. and his patent for detecting anomalous values highlight his commitment to improving financial data accuracy for small businesses.

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