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Vidhya Rohini Raman

from San Jose, CA
Age ~40

Vidhya Raman Phones & Addresses

  • San Jose, CA
  • Allen, TX
  • Sunnyvale, CA
  • Kentwood, MI
  • Richardson, TX

Work

Company: Fractal analytics inc Apr 2011 Position: Business consultant

Education

School / High School: The University of Texas at Dallas- Dallas, TX Aug 2008 Specialities: Masters in Information Technology Management

Skills

KPI Reporting • Data Warehouse and Data Mart Design. Ent... • Business Intelligence • Business Objects • Requirements • Subject Matter Expertise

Resumes

Resumes

Vidhya Raman Photo 1

Vidhya Raman

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Vidhya Raman Photo 2

Vidhya Raman

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Work:
Polaris Financial Technology Limited Aug 2004 - Apr 2007
Human Resources Executive
Vidhya Raman Photo 3

Vidhya Raman Sunnyvale, CA

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Work:
Fractal Analytics Inc

Apr 2011 to 2000
Business Consultant

Fractal Analytics Inc

May 2010 to Apr 2011
Senior Analyst

Burns Controls Company
Dallas, TX
Jan 2010 to May 2010
Business Consultant

The University of Texas at Dallas
Dallas, TX
May 2009 to Dec 2009
Teaching Assistant

Infosys Technologies Limited, India

Jun 2006 to Jul 2008
Module Lead

Education:
The University of Texas at Dallas
Dallas, TX
Aug 2008 to May 2010
Masters in Information Technology Management

Anna University
Chennai, Tamil Nadu
Jul 2002 to May 2006
Bachelor of Electrical and Electronics Engineering in Quality Management

Skills:
KPI Reporting, Data Warehouse and Data Mart Design. Enterprise Software, Business Intelligence, Business Objects, Requirements, Subject Matter Expertise

Publications

Us Patents

Methods And Apparatus For Fraud Detection

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US Patent:
20200242610, Jul 30, 2020
Filed:
Jan 24, 2019
Appl. No.:
16/256903
Inventors:
- Bentonville AR, US
Vidhya Raman - San Jose CA, US
Hui-Min Chen - Pleasanton CA, US
Sangita Fatnani - Cupertino CA, US
International Classification:
G06Q 20/40
G06K 9/62
G06F 17/11
Abstract:
This application relates to apparatus and methods for identifying fraudulent transactions. A computing device receives return data identifying the return of at least one item. The computing device obtains modified strategy data identifying at least one rule of a modified strategy. The rule may be based on the application of at least one discrete stochastic gradient descent algorithm to an initial strategy. The computing device applies the modified strategy to the received return data identifying the return of the at least one item, and determines whether the return of the at least one item is fraudulent based on the application of the modified strategy. The computing device generates fraud data identifying whether the return of the at least one item is fraudulent based on the determination, and may transmit the fraud data to another computing device to indicate whether the return is fraudulent.
Vidhya Rohini Raman from San Jose, CA, age ~40 Get Report