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Ranjith Unnikrishnan Phones & Addresses

  • 5034 Xavier Cmn, Fremont, CA 94555
  • Mountain View, CA
  • 240 Melwood Ave, Pittsburgh, PA 15213 (412) 683-0947
  • 5553 Beacon St, Pittsburgh, PA 15217 (412) 421-9101
  • 5553 Beacon St, Pittsburgh, PA 15217 (412) 512-6140

Work

Company: Lyft May 2019 Position: Staff engineer at level 5

Education

Degree: Doctorates, Doctor of Philosophy School / High School: Carnegie Mellon University 2002 to 2008 Specialities: Robotics

Skills

Computer Science • C++ • C • Distributed Systems • Algorithms • Software Development • Research • Automation • Machine Learning • Computer Vision • Image Processing • Software Engineering • Matlab • Python • Robotics • Linux • Programming • Artificial Intelligence

Industries

Information Technology And Services

Resumes

Resumes

Ranjith Unnikrishnan Photo 1

Staff Engineer At Level 5

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Location:
701 south Santa Fe St, Pauls Valley, OK 73075
Industry:
Information Technology And Services
Work:
Lyft
Staff Engineer at Level 5

Google
Senior Software Engineer at Google

Google Aug 2012 - Feb 2013
Product Manager

Google Aug 2012 - Feb 2013
Software Engineer
Education:
Carnegie Mellon University 2002 - 2008
Doctorates, Doctor of Philosophy, Robotics
Carnegie Mellon University 2000 - 2002
Master of Science, Masters, Robotics
Indian Institute of Technology, Kharagpur 1996 - 2000
Bachelors, Bachelor of Technology, Electronics
Abu Dhabi Indian School
Carnegie Mellon University;Ph.d, Robotics;2002 – 2008;
Doctorates, Doctor of Philosophy, Robotics
Skills:
Computer Science
C++
C
Distributed Systems
Algorithms
Software Development
Research
Automation
Machine Learning
Computer Vision
Image Processing
Software Engineering
Matlab
Python
Robotics
Linux
Programming
Artificial Intelligence

Publications

Us Patents

Method And Device For Authintication Of Live Human Faces Using Infra Red Images

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US Patent:
20140071293, Mar 13, 2014
Filed:
Sep 12, 2012
Appl. No.:
13/611977
Inventors:
Ranjith UNNIKRISHNAN - Mountain View CA, US
Assignee:
GOOGLE INC. - Mountain View CA
International Classification:
H04N 5/33
US Classification:
348164, 348E0509
Abstract:
A security device for identifying a person makes two images of a person to detect spoofing. The first image is a conventional visible image and the second image is an infrared image. Both images are analyzed to determine whether they represent a real person or not. If a placard or active display device is presented to the security device to spoof the real person, the infrared image of the placard or display device is recognized not to have the same characteristics as the infrared image of a real person.

Systems And Methods For Encoding And Searching Scenario Information

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US Patent:
20210406262, Dec 30, 2021
Filed:
Jun 30, 2020
Appl. No.:
16/917336
Inventors:
- San Francisco CA, US
Ranjith Unnikrishnan - Fremont CA, US
Assignee:
Lyft, Inc. - San Francisco CA
International Classification:
G06F 16/2458
G06F 16/248
Abstract:
Systems, methods, and non-transitory computer-readable media can receive a query specifying at least one example scenario. At least one image representation of the at least one example scenario can be encoded based on the query to produce at least one encoded representation. An embedding of the at least one representation of the at least one example scenario can be generated based on the at least one encoded representation. At least one scenario that is similar to the at least one example scenario can be identified based at least in part on the embedding of the at least one representation of the at least one example scenario and an embedding representing the at least one scenario. Information describing the at least one identified scenario can be provided in response to the query.

Approaches For Encoding Environmental Information

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US Patent:
20210124350, Apr 29, 2021
Filed:
Oct 23, 2019
Appl. No.:
16/661402
Inventors:
- San Francisco CA, US
David Tse-Zhou Lu - Menlo Park CA, US
Sheng Yang - Palo Alto CA, US
Ranjith Unnikrishnan - Fremont CA, US
Emilie Jeanne Anne Danna - Sunnyvale CA, US
Weiyi Hou - Mountain View CA, US
Suneet Rajendra Shah - San Francisco CA, US
Ying Liu - Los Altos CA, US
Assignee:
Lyft, Inc. - San Francisco CA
International Classification:
G05D 1/00
Abstract:
Systems, methods, and non-transitory computer-readable media can access a plurality of parameter-based encodings providing a structured representation of an environment captured by one or more sensors associated with a plurality of vehicles traveling through the environment. A given parameter-based encoding of the environment identifies one or more agents that were detected by a vehicle within the environment and respective location information for the one or more agents within the environment. The plurality of parameter-based encodings can be clustered into one or more clusters of parameter-based encodings. At least one scenario associated with the environment can be determined based at least in part on the one or more clusters of parameter-based encodings.

Approaches For Encoding Environmental Information

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US Patent:
20210124355, Apr 29, 2021
Filed:
Oct 23, 2019
Appl. No.:
16/661373
Inventors:
- San Francisco CA, US
David Tse-Zhou Lu - Menlo Park CA, US
Sheng Yang - Palo Alto CA, US
Ranjith Unnikrishnan - Fremont CA, US
Emilie Jeanne Anne Danna - Sunnyvale CA, US
Weiyi Hou - Mountain View CA, US
Suneet Rajendra Shah - San Francisco CA, US
Ying Liu - Los Altos CA, US
Assignee:
Lyft, Inc. - San Francisco CA
International Classification:
G05D 1/02
G05D 1/00
Abstract:
Systems, methods, and non-transitory computer-readable media can determine sensor data captured by at least one sensor of a vehicle while navigating an environment over a period of time. Information describing one or more agents associated with the environment during the period of time can be determined based at least in part on the captured sensor data. A parameter-based encoding describing the one or more agents associated with the environment during the period of time can be generated based at least in part on the determined information and a scenario schema, wherein the parameter-based encoding provides a structured representation of the information describing the one or more agents associated with the environment. A scenario represented by the parameter-based encoding can be determined based at least in part on a cluster of parameter-based encodings to which the parameter-based encoding is assigned.
Ranjith Unnikrishnan from Fremont, CA, age ~45 Get Report