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Vikas Gottemukkula

from Kansas City, MO
Age ~37
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Related to:
Satyanarayan Gottemukkula
Connected to:
Brad L Gottenberg, 33Jan Gottenborg, 63Amber R Gotter, 32Bruce A Gotter, 58Charles F Gotter, 84James A Gotterba, 72Piper J Gottes, 66Amy Gottesdiener, 61Elise B Gottesfeld, 87Shimshon S Gottesfeld, 83

Vikas Gottemukkula Phones & Addresses

  • Kansas City, MO
  • Vienna, VA
  • Kansas City, KS

Work

Company: Eyeverify Dec 2012 Position: Biometric research and development intern

Education

School / High School: University of Missouri-Kansas City- Kansas City, MO 2011 Specialities: Doctor of Philosophy (Ph.D.)

Skills

Machine Learning • Signal Processing • Image Processing • Pattern Recognition • Matlab • Algorithms • Computer Vision • C • Simulations • Biomedical Engineering • Data Mining • Biometrics • Python • Computational Intelligence • Algorithm Design • Deep Learning

Industries

Information Technology And Services

Resumes

Resumes

Vikas Gottemukkula Photo 1

Senior Research Scientist

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Location:
4944 Grand Ave, Kansas City, MO 64112
Industry:
Information Technology And Services
Work:
Zoloz
Senior Research Scientist
Eyeverify Oct 1, 2014 - Dec 2016
Biometric and Computer Vision Scientist
Umkc Jan 2011 - Dec 2012
Graduate Research Assistant
Eyeverify May 2012 - Aug 2012
Biometric Research and Development Intern
Umkc Jan 2012 - May 2012
Graduate Teaching Assistant
Education:
University of Missouri - Kansas City 2011 - 2014
Doctorates, Doctor of Philosophy, Computer Engineering, Philosophy University of Missouri - Kansas City 2008 - 2010
Master of Science, Masters, Electronics Engineering Jawaharlal Nehru Technological University 2004 - 2008
Bachelors, Bachelor of Technology, Electronics, Engineering, Communications
Skills:
Machine Learning
Signal Processing
Image Processing
Pattern Recognition
Matlab
Algorithms
Computer Vision
C
Simulations
Biomedical Engineering
Data Mining
Biometrics
Python
Computational Intelligence
Algorithm Design
Deep Learning
Vikas Gottemukkula Photo 2

Vikas Gottemukkula Kansas City, MO

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Work:
EyeVerify

Dec 2012 to 2000
Biometric Research and Development Intern
UMKC

Jan 2011 to Dec 2012
Graduate Research Assistant
EyeVerify
Kansas City, KS
May 2012 to Aug 2012
Biometric Research and Development Intern
UMKC
Kansas City, MO
Jan 2012 to May 2012
Graduate Teaching Assistant
Education:
University of Missouri-Kansas City
Kansas City, MO
2011
Doctor of Philosophy (Ph.D.)
University of Missouri-Kansas City
Kansas City, MO
2008 to 2010
Master of Science in Electrical and Electronics Engineering
Jawaharlal Nehru Technological University
2004 to 2008
Bachelor of Technology in Electronics and Communications Engineering

Publications

Us Patents

Quality Metrics For Biometric Authentication

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US Patent:
8483450, Jul 9, 2013
Filed:
Aug 10, 2012
Appl. No.:
13/572267
Inventors:
Reza Derakhshani - Roeland Park KS, US
Vikas Gottemukkula - Kansas City MO, US
Assignee:
EyeVerify LLC - Kansas City KS
International Classification:
G06K 9/00
US Classification:
382117, 382115, 382162
Abstract:
This specification describes technologies relating to biometric authentication based on images of the eye. In general, one aspect of the subject matter described in this specification can be embodied in methods that include obtaining a first image of an eye including a view of the white of the eye. The method may further include determining metrics for the first image, including a first metric for reflecting an extent of one or more connected structures in the first image that represents a morphology of eye vasculature and a second metric for comparing the extent of eye vasculature detected across different color components in the first image. A quality score may be determined based on the metrics for the first image. The first image may be rejected or accepted based on the quality score.

Quality Metrics For Biometric Authentication

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US Patent:
20140044319, Feb 13, 2014
Filed:
Jun 6, 2013
Appl. No.:
13/912032
Inventors:
Vikas Gottemukkula - Kansas City MO, US
International Classification:
A61B 5/117
US Classification:
382117
Abstract:
This specification describes technologies relating to biometric authentication based on images of the eye. In general, one aspect of the subject matter described in this specification can be embodied in methods that include obtaining a first image of an eye including a view of the white of the eye. The method may further include determining metrics for the first image, including a first metric for reflecting an extent of one or more connected structures in the first image that represents a morphology of eye vasculature and a second metric for comparing the extent of eye vasculature detected across different color components in the first image. A quality score may be determined based on the metrics for the first image. The first image may be rejected or accepted based on the quality score.

Texture Features For Biometric Authentication

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US Patent:
20140044320, Feb 13, 2014
Filed:
Jul 24, 2013
Appl. No.:
13/950086
Inventors:
Vikas Gottemukkula - Kansas City MO, US
Casey Hughlett - Lenexa KS, US
Assignee:
EyeVerify LLC - Kansas City KS
International Classification:
G06K 9/00
US Classification:
382117
Abstract:
In general, one aspect of the subject matter described can be embodied in methods that include obtaining one or more image regions from a first image of an eye. Each of the image regions may include a view of a respective portion of the white of the eye. The method may further include applying several distinct filters to each of the image regions to generate a plurality of respective descriptors for the region. The several distinct filters may include convolutional filters that are each configured to describe one or more aspects of an eye vasculature and in combination describe a visible eye vasculature in a feature space. A match score may be determined based on the generated descriptors and based on one or more descriptors associated with a second image of eye vasculature.

Texture Features For Biometric Authentication

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US Patent:
8369595, Feb 5, 2013
Filed:
Aug 10, 2012
Appl. No.:
13/572188
Inventors:
Reza Derakhshani - Roeland Park KS, US
Vikas Gottemukkula - Kansas City MO, US
Casey Hughlett - Lenexa KS, US
Assignee:
EyeVerify LLC - Lenexa KS
International Classification:
G06K 9/00
US Classification:
382128, 382117
Abstract:
This specification describes technologies relating to biometric authentication based on images of the eye. In general, one aspect of the subject matter described in this specification can be embodied in methods that include obtaining one or more image regions from a first image of an eye. Each of the image regions may include a view of a respective portion of the white of the eye. The method may further include applying several distinct filters to each of the image regions to generate a plurality of respective descriptors for the region. The several distinct filters may include convolutional filters that are each configured to describe one or more aspects of an eye vasculature and in combination describe a visible eye vasculature in a feature space. A match score may be determined based on the generated descriptors and based on one or more descriptors associated with a second image of eye vasculature.

Multi-Sensor Motion Analysis To Check Camera Pipeline Integrity

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US Patent:
20220351391, Nov 3, 2022
Filed:
Apr 29, 2021
Appl. No.:
17/244657
Inventors:
- Palo Alto CA, US
Vikas Gottemukkula - Kansas City KS, US
Yash Joshi - Kansas City MO, US
Sashi Kanth Saripalle - Overland Park KS, US
Tetyana Anisimova - Shawnee KS, US
International Classification:
G06T 7/246
G06T 7/215
G06T 7/262
G06K 9/00
Abstract:
This specification includes a method that includes receiving, at one or more processing devices at one or more locations, one or more image frames; receiving a set of signals representing outputs of one or more sensors of a device; estimating, based on the one or more image frames, a first set of one or more motion values; estimating, based on the set of signals, a second set of one or more motion values; determining that a degree of correlation between (i) a first motion represented by the first set of one or more motion values and (ii) a second motion represented by the second set of one or more motion values fails to satisfy a threshold condition; and in response to determining that the degree of correlation fails to satisfy the threshold condition, determining presence of an adverse condition associated with the device.

Fusing Multi-Spectral Images For Identity Authentication

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US Patent:
20200302149, Sep 24, 2020
Filed:
Mar 22, 2019
Appl. No.:
16/361453
Inventors:
- George Town, KY
Vikas Gottemukkula - Kansas City KS, US
Assignee:
Alibaba Group Holding Limited - George Town
International Classification:
G06K 9/00
G06N 3/08
G06K 9/62
Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining the identity of a user. In one aspect, a method comprises: obtaining a multi-spectral image that depicts an eye of a user, wherein the multi-spectral image comprises a plurality of registered two-dimensional channels, and each two-dimensional channel corresponds to a different spectrum of the multi-spectral image; processing the multi-spectral image using an encoder neural network to generate a fused image, wherein the fused image has a single two-dimensional channel; determining a set of features characterizing the eye of the user from the fused image; and determining an identity of the user based at least in part on the set of features characterizing the eye of the user.

Spoof Detection By Comparing Images Captured Using Visible-Range And Infrared (Ir) Illuminations

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US Patent:
20200293640, Sep 17, 2020
Filed:
Mar 15, 2019
Appl. No.:
16/355374
Inventors:
- George Town, KY
Vikas Gottemukkula - Kansas City KS, US
Assignee:
Alibaba Group Holding Limited - George Town
International Classification:
G06F 21/32
G06K 9/00
Abstract:
Technology described herein can be embodied in a method for preventing access to a secure system based on determining a captured image to be of an alternative representation of a live person. The method includes capturing a first image and a second image of a subject illuminated by electromagnetic radiation in a first and a second wavelength ranges, respectively. The method also includes extracting, from the first image, a first portion representative of a sclera region of the subject, and from the second image, a second portion representative of the same region. It is determined that each of the first portion and the second portion includes features representative of vasculature in the sclera region, and in response, the subject in the image is identified to be an alternative representation of a live person. Upon search identification, the method includes preventing access to the secure system.

Neural Networks For Biometric Recognition

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US Patent:
20200143137, May 7, 2020
Filed:
Nov 7, 2018
Appl. No.:
16/183274
Inventors:
- George Town, KY
Vikas Gottemukkula - Kansas City KS, US
Assignee:
Alibaba Group Holding Limited - George Town
International Classification:
G06K 9/00
G06N 3/08
A61B 5/1171
G06N 3/04
Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an encoder neural network having multiple encoder neural network parameters. The encoder neural network is configured to process a biometric data sample in accordance with current values of encoder neural network parameters to generate as output an embedded representation of the biometric data sample. The embedded representation includes: (i) an inter-class embedded representation, and (ii) an intra-class embedded representation that is different than the inter-class embedded representation.
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Vikas Gottemukkula from Kansas City, MO, age ~37 Get Report