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Kaushiki Nag

from San Jose, CA
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Connected to:
Indira Nag, 91Mihir K Nag, 68Tinku Nag, 48Chiranjeevi K Naga, 40Jamal Naga, 60Maria G Naga, 62Mary Naga, 77Pavani T Naga, 35Pradeep Naga, 36Tarlana V Naga, 32

Kaushiki Nag Phones & Addresses

  • San Jose, CA
  • Sunnyvale, CA
  • San Bruno, CA

Work

Company: Walmart labs Sep 2014 to Aug 2017 Position: Senior software engineer

Education

Degree: Masters School / High School: University of Minnesota 2011 to 2013 Specialities: Computer Science

Skills

Programming • Java • C • C++ • Perl • Unix • Unix Shell Scripting • Hadoop • Hive • Mysql • Big Data • Mapreduce • Computer Science • Machine Learning • Distributed Systems • Data Mining • Algorithms • Software Development

Industries

Computer Software

Resumes

Resumes

Kaushiki Nag Photo 1

Staff Software Engineer

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Location:
301 west Washington Ave, Sunnyvale, CA 94086
Industry:
Computer Software
Work:
Walmart Labs Sep 2014 - Aug 2017
Senior Software Engineer
Walmart Labs Sep 2014 - Aug 2017
Staff Software Engineer
Walmart Labs Sep 2013 - Sep 2014
Software Engineer
University of Minnesota Jan 2013 - May 2013
Graduate Research Assistant
Honeywell Jun 2012 - Dec 2012
Software Co-Op
Education:
University of Minnesota 2011 - 2013
Masters, Computer Science University of Mumbai 2005 - 2009
Bachelors, Electronics Engineering
Skills:
Programming
Java
C
C++
Perl
Unix
Unix Shell Scripting
Hadoop
Hive
Mysql
Big Data
Mapreduce
Computer Science
Machine Learning
Distributed Systems
Data Mining
Algorithms
Software Development

Publications

Us Patents

Automatic Personalized Email Triggers

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US Patent:
20220215428, Jul 7, 2022
Filed:
Mar 28, 2022
Appl. No.:
17/706300
Inventors:
- Bentonville AR, US
Sushant Kumar - Sunnyvale CA, US
Kaushiki Nag - Santa Clara CA, US
Venkata Syam Prakash Rapaka - Cupertino CA, US
Assignee:
Walmart Apollo, LLC - Bentonville AR
International Classification:
G06Q 30/02
Abstract:
A method including training a logistic regression model to create a trained model to provide probabilities of users clicking on emails of one or more email campaigns within each of multiple different time periods. Input predictor variables of the logistic regression model include (i) user feature data including personal user features and online activity history for users in the multiple different time periods and (ii) email feature data including sent times and item category data for multiple different emails in the one or more email campaigns. Output dependent variables of the logistic regression model include responses by the users to the one or more email campaigns. The method also includes triggering sending a first email of the one or more email campaigns to a first user of the users at a selected time period based at least in part on the trained model. Other embodiments are disclosed.

Systems And Methods For Webpage Personalization

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US Patent:
20200177701, Jun 4, 2020
Filed:
Feb 3, 2020
Appl. No.:
16/780800
Inventors:
- Bentonville AR, US
Kannan Achan - Saratoga CA, US
Kaushiki Nag - Santa Clara CA, US
Sushant Kumar - Sunnyvale CA, US
Assignee:
Walmart Apollo, LLC - Bentonville AR
International Classification:
H04L 29/08
G06Q 30/02
Abstract:
A system can include one or more processing modules and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processing modules and perform receiving, from an electronic device, a search query from a user of a plurality of users; processing first data; and facilitating displaying a set of items. Processing the first data can comprise determining one or more keywords by capturing the one or more keywords during a time window; creating a feature set of second data associated with at least a portion of the plurality of users; determining a set of items of the item set as being based at least in part on an item vector representation and a keyword vector representation; determining a respective purchase probability associated with each item of the set of items of the item set; ranking the set of items.

Automatic Personalized Image-Based Search

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US Patent:
20190236095, Aug 1, 2019
Filed:
Jan 28, 2019
Appl. No.:
16/259822
Inventors:
- Bentonville AR, US
Sushant Kumar - Sunnyvale CA, US
Kaushiki Nag - Santa Clara CA, US
Venkata Syam Prakash Rapaka - Cupertino CA, US
Assignee:
Walmart Apollo, LLC - Bentonville AR
International Classification:
G06F 16/535
G06F 16/56
G06F 16/9535
G06N 3/08
Abstract:
A method including training a recurrent neural network model to create a trained model based at least in part on: (a) first images associated with first items on a website, (b) first search terms used by users of the website to search for the first items on the website, and (c) personal features of the users. The method also can include receiving an input image that was uploaded by a current user. The method additionally can include obtaining a user encoded representation vector for the current user based on a set of personal features of the current user. The method further can include generating an image encoded representation vector for the input image. The method additionally can include deriving search terms that are personalized to the current user for the one or more items depicted in the input image, using the trained model and based on the user encoded representation vector for the current user and the image encoded representation vector for the input image. Other embodiments are disclosed.

Automatic Personalized Email Triggers

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US Patent:
20190236643, Aug 1, 2019
Filed:
Jan 28, 2019
Appl. No.:
16/259626
Inventors:
- Bentonville AR, US
Sushant Kumar - Sunnyvale CA, US
Kaushiki Nag - Santa Clara CA, US
Venkata Syam Prakash Rapaka - Cupertino CA, US
Assignee:
Walmart Apollo, LLC - Bentonville AR
International Classification:
G06Q 30/02
Abstract:
A method including tracking first data including responses by users to email campaigns. The method also can include generating a user feature set for the users, the user feature set including personal features of each of the users and online activity history for each of the users across a first set of time periods. The method additionally can include generating an email feature set for the emails in the email campaigns. The method further can include training a logistic regression model to create a trained model using the first data, the user feature set, and the email feature set to provide a probability of a user of the users clicking on an email of the emails within each time period of a second set of time periods. The method additionally can include triggering sending a first email of the email campaigns to a first user of the users at a selected time period of the second set of time periods based at least in part on the trained model. Other embodiments are disclosed.

Systems And Methods For Webpage Personalization

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US Patent:
20180218087, Aug 2, 2018
Filed:
Jan 31, 2017
Appl. No.:
15/420822
Inventors:
- Bentonville AR, US
Kannan Achan - Saratoga CA, US
Kaushiki Nag - Santa Clara CA, US
Sushant Kumar - Sunnyvale CA, US
Assignee:
WAL-MART STORES, INC. - Bentonville AR
International Classification:
G06F 17/30
G06Q 30/02
H04L 29/08
Abstract:
In some embodiments, a method can comprise receiving a search query from a search by a user during a browse session, receiving one or more items from an item database in response to the search query, and receiving one or more previous search queries from a search database, the one or more previous search queries related to the search query. In many embodiments, the method can further comprise determining a purchase probability associated with a first item of the one or more items based at least in part on a first item score for the first item, ranking the one or more items based at least in part on the purchase probability associated with the first item of the one or more items, and facilitating display of the ranking of the one or more items. Other embodiments of related methods and systems are also provided.
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Kaushiki Nag from San Jose, CA Get Report