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Beena Khushalani

from Moorpark, CA
Age ~53
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Also known as:
Beena K Kumar, Vena Khushalani, Beena I
Phone and address:
13752 Elkton Ct, Moorpark, CA 93021
Related to:
Kishor Kumar, 58
Connected to:
Vaishali S Khushalani, 52Niyaz Khusnatdinov, 63Vanna Khut, 65Saul I Khutaina, 68Nataliya Khutorna, 51Tanya Khutorsky, 52George Khutoryansky, 51Seema Khutti, 45Alexander T Khuu, 54Anh P Khuu, 56

Beena Khushalani Phones & Addresses

  • 13752 Elkton Ct, Moorpark, CA 93021
  • 1706 Blazewood St, Simi Valley, CA 93063
  • 5569 Cochran St, Simi Valley, CA 93063
  • Los Angeles, CA
  • Ventura, CA
  • Doral, FL

Resumes

Resumes

Beena Khushalani Photo 1

Baba Nebhraj School

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Location:
Los Angeles, CA
Industry:
Financial Services
Work:
Bank of America
Svp, Senior Technology Manager
Bank of America Feb 2015 - Sep 2017
Senior Vice President, Business Solutions Technology Manager
Bank of America Dec 2009 - Jan 2015
Svp, Senior Application Development Manager
Bank of America Mar 2007 - Nov 2009
Senior Vice President, Senior Applications Development Manager
Bank of America Aug 2003 - Feb 2007
Vp, Senior Technology Manager
Education:
The Wharton School 2016 - 2018
University of Southern California 1997 - 1998
Masters, Engineering Department of Management Studies, Nsut 1988 - 1992
Bachelor of Engineering, Bachelors, Engineering Delhi College of Engineering 1988 - 1992
Bachelor of Engineering, Bachelors, Engineering Baba Nebhraj School
Skills:
It Strategy
Business Analysis
Project Management
Solution Architecture
Application Lifecycle Management
Team Leadership
Business Process Re Engineering
Database Design
Web Application Design
Pega Prpc
Relationship Management
Beena Khushalani Photo 2

Beena Khushalani

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Location:
United States

Business Records

Name / Title
Company / Classification
Phones & Addresses
Beena Khushalani
President
LEO INFO SOLUTIONS USA, INC
Nonclassifiable Establishments
13752 Elkton Ct, Moorpark, CA 93021

Publications

Us Patents

Automated Categorization And Assembly Of Low-Quality Images Into Electronic Documents

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US Patent:
20220350999, Nov 3, 2022
Filed:
May 3, 2021
Appl. No.:
17/306495
Inventors:
- Charlotte NC, US
Sean Michael Byrne - Tampa FL, US
Syed Talha - McKinney TX, US
Aftab Khan - Richardson TX, US
Beena Khushalani - Moorpark CA, US
Sharad K. Kalyani - Coppell TX, US
International Classification:
G06K 9/46
G06F 40/20
G06K 9/00
G06K 9/40
G06N 20/00
G06F 16/93
Abstract:
An apparatus includes a memory and processor. The memory stores document categories, text generated from an image a physical document page, and a machine learning algorithm. The text includes errors associated with noise in the image. The machine learning algorithm is configured to extract features associated with natural language processing and features associated with the errors from the text. The machine learning algorithm is also configured to generate a feature vector that includes the first and second pluralities of features, and to generate, based on the feature vector, a set of probabilities, each of which is associated with a document category and indicates a probability that the physical document from which the text was generated belongs to that document category. The processor applies the machine learning algorithm to the text, to generate the set of probabilities, identifies a largest probability, and assigns the image to the associated document category.

System For Electronic Identification Of Attributes For Performing Maintenance, Monitoring, And Distribution Of Designated Resource Assets

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US Patent:
20220237035, Jul 28, 2022
Filed:
Jan 22, 2021
Appl. No.:
17/155348
Inventors:
- Charlotte NC, US
Peter Michael Farrell - Bridgewater NJ, US
Aftab Khan - Richardson TX, US
Beena Khushalani - Moorpark CA, US
Ashwin Roongta - East Brunswick NJ, US
Assignee:
BANK OF AMERICA CORPORATION - Charlotte NC
International Classification:
G06F 9/50
G06F 16/25
G06N 20/00
Abstract:
Embodiments of the present invention provide a system for electronic identification of attributes for performing maintenance, monitoring, and distribution of designated resource assets. In particular, the system may be configured to extract one or more legacy resources from a data repository of an entity system associated with an entity, wherein the legacy resources are in a first format, convert the one or more legacy resources from the first format to a second format, process the one or more legacy resources, via one or more machine learning models, identify one or more attributes based on processing the one or more legacy resources via the one or machine learning models, and implement one or more actions based on the one or more attributes.
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Beena Khushalani from Moorpark, CA, age ~53 Get Report