TeleNav - Sunnyvale since Jan 2011
Sr. Director, Mobile Advertising, Local Search & Discovery Products
Yahoo! 2006 - Jan 2011
Director of Product - Big Data Systems & Analytics, and Advertising
Oracle 2005 - 2006
Product Management
Nextance 2002 - 2005
Product Management
OneBuild 1999 - 2002
VP Product Management & Engineering
Education:
Louisiana State University and Agricultural and Mechanical College 1990 - 1992
Birla Institute of Technology 1985 - 1989
Skills:
Product Management Big Data Analytics Cloud Computing Enterprise Software Scalability Product Development Mobile Applications Strategy Integration Cross Functional Team Leadership Start Ups Saas Distributed Systems Display Advertising Business Intelligence Online Advertising Machine Learning Mobile Advertising Business Development Engineering Leadership Search Advertising Product Strategy Mobile Local Search Social Media Monetization Software As A Service Search Analytics Predictive Analytics Ios Statistical Learning Social Analytics Management Leadership Executive Management Hadoop Scala
Aliasgar Mumtaz Husain - Milpitas CA, US Shirish Kumar - Cupertino CA, US
Assignee:
TELENAV, INC. - Sunnyvale CA
International Classification:
G01C 21/00
US Classification:
701400
Abstract:
A method of operation of a navigation system includes: locating a target POI; generating a relationship for the target POI and a related POI; and generating a travel route based on the relationship to the target POI for displaying on a device.
Massive Scale Heterogeneous Data Ingestion And User Resolution
- Costa Mesa CA, US Prashant Kumar Sahay - West Windsor NJ, US Mervyn Lally - Laguna Niguel CA, US Shirish Kumar - Saratoga CA, US Sanskar Sahay - Princeton NJ, US
International Classification:
G06F 17/30 G06Q 40/02
Abstract:
This disclosure relates to data association, attribution, annotation, and interpretation systems and related methods of efficiently organizing heterogeneous data at a massive scale. Incoming data is received and extracted for identifying information (“information”). Multiple dimensionality reducing functions are applied to the information, and based on the function results, the information are grouped into sets of similar information. Filtering rules are applied to the sets to exclude non-matching information in the sets. The sets are then merged into groups of information based on whether the sets contain at least one common information. A common link may be associated with information in a group. If the incoming data includes the identifying information associated with to the common link, the incoming data is assigned the common link. In some embodiments, incoming data are not altered but assigned into domains.