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Dhananjay Dilip Kulkarni, 399721 NE 183Rd St UNIT D, Bothell, WA 98011

Dhananjay Kulkarni Phones & Addresses

9721 NE 183Rd St UNIT D, Bothell, WA 98011   

4035 145Th Ave NE #4, Bellevue, WA 98007   

Seattle, WA   

Redmond, WA   

Mentions for Dhananjay Dilip Kulkarni

Dhananjay Kulkarni resumes & CV records

Resumes

Dhananjay Kulkarni Photo 28

Software Development Engineer At Microsoft

Position:
Software Development Engineer at Microsoft
Location:
Greater Seattle Area
Industry:
Information Technology and Services
Work:
Microsoft - Bellevue since Feb 2012
Software Development Engineer
Carnegie Mellon University Aug 2010 - Feb 2012
Student - MSIT (Very Large Information Systems)
Microsoft - Greater Seattle Area May 2011 - Aug 2011
SDE Intern
Amazon May 2009 - Jul 2010
Software Development Engineer
Versata Jul 2008 - Apr 2009
Technical Associate
Versata Jul 2007 - Jun 2008
Technical Analyst
Education:
ABV Indian Institute of Information Technology and Management, Gwalior 2002 - 2007
Integrated Post Graduate (BTech. + MTech. - IT), Information Technology
HRI
Skills:
Java, Hadoop, Data Structures, Web Development, Algorithms, Distributed Systems
Dhananjay Kulkarni Photo 29

Dhananjay Kulkarni

Location:
United States
Education:
Welingkar Institute of Management 2007 - 2008
B.E.,M.B.A., Renewable Energy Sources.
Dhananjay Kulkarni Photo 30

Dhananjay Kulkarni

Location:
United States
Dhananjay Kulkarni Photo 31

Dhananjay Kulkarni

Location:
United States

Publications & IP owners

Us Patents

Discovering Authoritative Images Of People Entities

US Patent:
2014017, Jun 26, 2014
Filed:
Dec 20, 2012
Appl. No.:
13/722085
Inventors:
- Redmond WA, US
Padma Priya GAGGARA - Redmond WA, US
Prakash Asirvatham ARUL - Redmond WA, US
Mohammad Adil HAFEEZ - Redmond WA, US
Dhananjay Dilip KULKARNI - Seattle WA, US
Kancheng CAO - Bothell WA, US
Assignee:
MICROSOFT CORPORATION - Redmond WA
International Classification:
G06K 9/00
US Classification:
382195
Abstract:
Systems, methods, and computer storage media for discovering authoritative images of people entities are provided. Selections of person entities are received. Authoritative URLs and authoritative images for the person entities are identified. Once the authoritative images are identified, features are extracted. Queries for the person entities are identified by mining search engine logs. The queries and features can be utilized to construct candidate queries to identify and retrieve candidate image URLs. Candidate features are extracted for each candidate image associated with the candidate image URLs. Training data may be utilized to train a classifier that can be run on each candidate image. Each candidate image can then be tagged with an entity ID tag. Images with the entity ID tag can be ranked higher in search engine results page than images without the entity ID tag.

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