Doordash
Director of Engineering
Uber Mar 2015 - Jul 2019
Engineering Management and Leadership
Netflix Mar 2012 - Mar 2015
Manager, Cloud Platform Engineering
Nirmata Dec 1, 2014 - 2015
Advisor
Netflix Apr 2008 - Mar 2012
Cloud Systems and Platform Engineer
Education:
National University 2001 - 2003
Master of Science, Masters, Computer Science, Commerce, Electronics
Malnad College of Engineering, Hassan
Bachelor of Engineering, Bachelors, Computer Science, Electronics, Communication
Skills:
Distributed Systems Scalability Java Cloud Computing Web Services Amazon Web Services Agile Methodologies Rest Hadoop Big Data Web Applications Open Source Architecture Tomcat Spring Framework Object Oriented Design Amazon Ec2 Application Servers System Architecture Server Architecture Spring Nosql Representational State Transfer High Availability Apache Continuous Integration Ant Perforce Jms Mapreduce Engineering Management Architectures Web Servers Design Patterns Internationalization Ec2 Agile Servlets Cassandra Memcached Technical Leadership
Interests:
Facebook Engineering Entrepreneurship Travel Technology Distributed Systems Amazon Web Services Engineering Management Stanford Ai Class Cassandra (Database) Facebook Infrastructure Startup Founders and Entrepreneurs Varnish (Http Accelerator) Golf Natural Language Processing San Francisco Bay Area Nosql Programming Interviews
Darpan Dinker - San Jose CA, US Sudhir Tonse - Sunnyvale CA, US Suveen R. Nadipalli - Sunnyvale CA, US Pramod Gopinath - Union City CA, US
Assignee:
Sun Microsystems, Inc. - Santa Clara CA
International Classification:
G06F 15/16
US Classification:
709225, 709229, 713185
Abstract:
A system and method for controlling access to data in a distributed computer system. Distributed Token Manager (DTM) is a system-level service that coordinates read/write access of data objects (tokens) in a multi-process and multi-threaded environment. The DTM ensures that at any given time either: 1) One or more client processes or threads currently have read access rights to the data object, and no client processes or threads currently have write access rights to the data object; or 2) One client process or thread currently has write access to the data object and no other client processes or threads currently have read or write access rights to the data object. DTM also ensures that such coordination works smoothly even in the case of process/machine/network failure.
Distributed Token Manager With Transactional Properties
Darpan Dinker - Santa Clara CA, US Pramod Gopinath - Union City CA, US Suveen R. Nadipalli - Sunnyvale CA, US Sudhir Tonse - Sunnyvale CA, US
Assignee:
Sun Microsystems, Inc. - Santa Clara CA
International Classification:
G06F 15/13
US Classification:
709229, 707 8, 707203, 707205
Abstract:
A system and method for controlling access to data in a distributed computer system. Distributed Token Manager (DTM) is a system-level service that coordinates read/write access of data objects (tokens) in a multi-process and multi-threaded environment. The DTM may support a transactional model such that write operations to a data object performed by a client process or thread can be either committed or rolled back.
Presentation Of Content Items Based On Dynamic Monitoring Of Real-Time Context
The present invention provides systems and methods for providing real-time context-based content items to a user client system. Methods include dynamically monitoring a user client system to determine a real-time context of the user client system based on one or more of identifying one or more content keywords of an application operating on the user client system and/or one or more system capabilities of the user client system. One or more content items can be presented and changed based on changes detected in the real-time context of the user client system.
Sudhir Tonse - Fremont CA, US Muhammad Mohsin Hussain - San Jose CA, US David C. Sobotka - Redwood City CA, US Aftab Zia - Santa Clara CA, US Leejay Wu - Mountain View CA, US M. Sultan Khan - San Jose CA, US Brock D. LaPorte - San Carlos CA, US Mohan S. Rao - Sunnyvale CA, US
Assignee:
AOL Inc. - Dulles VA
International Classification:
G06Q 30/00
US Classification:
705 1454, 705 144, 705 1443, 705 1442, 705 10
Abstract:
Systems and methods are provided for increasing user response to advertisements. Methods include identifying a base request from an advertisement requester, identifying a first keyword and a second keyword associated with the base request, ranking the first keyword and the second keyword based on a user response history associated with the first keyword and the second keyword, and identifying the higher ranked of the first keyword and the second keyword to be used to dynamically alter the base request.
David C. Sobotka - Redwood City CA, US Aftab Zia - Santa Clara CA, US Sudhir Tonse - Fremont CA, US M. Sultan Khan - San Jose CA, US
Assignee:
AOL Inc. - Dulles VA
International Classification:
G06Q 30/00
US Classification:
705 1454, 705 144, 705 1443, 705 10
Abstract:
Systems and methods are provided for increasing user response to advertisements from advertisement suppliers obtained in response to keywords. In one embodiment, a method includes identifying a base request from an advertisement requester; identifying a first and second keyword associated with the base request, the first and second keyword having both previously been used in advertisement requests to a first advertisement supplier; ranking the first keyword and the second keyword based on a user response history for each of the first keyword and second keyword; and identifying the higher ranked of the first keyword and the second keyword to be used to dynamically alter the base request to form an altered request to be sent to the first advertisement supplier.
David C. Sobotka - Redwood CA, US Sudhir Tonse - Fremont CA, US Brock D. LaPorte - San Carlos CA, US Mike Macadaan - Livermore CA, US David J. Liu - Chevy Chase MD, US
Assignee:
AOL Inc. - Dulles VA
International Classification:
G06F 13/00 G06F 15/00
US Classification:
715758, 715745
Abstract:
A method for personalizing content for a particular user in a computing system comprising a user interface configured to display content. The method comprises identifying a long term profile having one or more features in a feature set and a long term level of importance associated with each term in the feature set, identifying a short term profile having one or more features in the feature set and a short term level of importance associated with each term in the feature set, identifying input related to the display of the one or more content items on the user interface, and using the input to modify the short term level of importance and the long term level of importance associated with each term in the feature set to form a modified user interest set.
Systems And Methods For Performing Machine-Implemented Tasks
David C. Sobotka - Redwood City CA, US Sudhir Tonse - Fremont CA, US Aftab Zia - Santa Clara CA, US
Assignee:
AOL Inc. - Dulles VA
International Classification:
G06F 9/46 G06Q 30/00 G06F 17/30
US Classification:
718100, 705 144, 707722
Abstract:
A task management system may be configured to select and/or perform one or more tasks. The task management system may be configured to create weighted groups of tasks to be performed in response to various triggering conditions. The task management system may include a value generation module, which may be configured to generate values used to select tasks from two or more of the weighted groups of tasks.
Justin M. Law - Maple Valley WA, US Muhammad Mohsin Hussain - San Jose CA, US David C. Sobotka - Redwood City CA, US Aftab Zia - Santa Clara CA, US Sudhir Tonse - Fremont CA, US Venkata S. J. R. Bhamidipati - Fremont CA, US M. Sultan Khan - San Jose CA, US
Assignee:
AOL Inc. - Dulles VA
International Classification:
G06Q 30/00
US Classification:
705 1454, 705 144, 705 1443, 705 1442, 705 10
Abstract:
Systems and methods are provided for dynamically ordering advertisements received from at least one advertisement supplier. In one embodiment, a method includes sending a request to at least a first advertisement supplier; receiving one or more advertisements from the at least first advertisement supplier; identifying a prioritizing parameter associated with each of the one or more advertisements; and dynamically ordering the one or more advertisements from the at least first advertisement supplier into two or more positions of a response based on the prioritizing parameter.
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Sudhir Tonse
Sudhir Tonse
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