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Sarabjot SinghUhland, TX

Sarabjot Singh Phones & Addresses

Kyle, TX   

1831 Wells Branch Pkwy, Austin, TX 78728   

Laurel, MD   

Mentions for Sarabjot Singh

Sarabjot Singh resumes & CV records

Resumes

Sarabjot Singh Photo 33

Staff Engineer

Location:
San Francisco, CA
Industry:
Wireless
Work:
Uhana Jan 2017 - Aug 2019
Principal Engineer, Wireless
Xran.org Jan 2017 - Jan 2018
Contributor
Intel Corporation May 2015 - Jan 2017
Research Scientist
Nokia Jan 2015 - May 2015
Senior Researcher
The University of Texas at Austin Jan 2011 - Dec 2014
Graduate Student
Nokia Bell Labs May 2013 - Aug 2013
Research Intern
Intel Corporation Jun 1, 2011 - Dec 1, 2011
Graduate Technical Intern
The University of Texas at Austin Aug 1, 2010 - Dec 1, 2010
Graduate Teaching Assistant
Qualcomm 2009 - 2009
Interim Engineering Intern
Indian Institute of Science 2008 - 2009
Research Intern
National Physical Laboratory 2007 - 2007
Intern
Vmware 2007 - 2007
Staff Engineer
Lightup Data 2007 - 2007
Senior Data Scientist
Education:
The University of Texas at Austin 2010 - 2014
Master of Science, Doctorates, Masters, Doctor of Philosophy, Electrical Engineering, Philosophy
Indian Institute of Technology, Guwahati 2006 - 2010
Bachelors, Bachelor of Technology, Communication, Engineering, Electronics
Skills:
Lte, Matlab, Wireless, Algorithms, C, Signal Processing, Latex, Machine Learning, Optimization, C++, Digital Signal Processors, Wireless Technologies, Embedded Systems, Systems Engineering, Simulations, Rf, Wifi, Wireless Networking, Fpga, Verilog, Qos, Perl, Radio Planning, Digital Signal Processing, Image Processing, Cdma, Cellular Communications, Simulink, Wireless Communications Systems, Ofdm, Ieee 802.11, Wireless System Engineering, Radio Resource Management, 4G, Telecommunications, Research, Mathematica, Python, 3Gpp, Qoe, Statistics, Information Theory, Data Science, 5G, Ran, Access Networks, Anomaly Detection, Root Cause Analysis, 5G New Radio
Languages:
Punjabi
English
Hindi
Certifications:
Machine Learning
Machine Learning: Classification
Neural Networks and Deep Learning
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
Structuring Machine Learning Projects
Convolutional Neural Networks
Deep Learning Specialization
License U3Aw4E7Qms5F
License E8Wxaydtp6Gh
Coursera Course Certificates, License U3Aw4E7Qms5F
Coursera Course Certificates, License E8Wxaydtp6Gh
Sarabjot Singh Photo 34

Senior Implementation Analyst

Location:
Austin, TX
Industry:
Information Technology And Services
Work:
Kantar
Senior Implementation Analyst
Wns Global Services Jul 2009 - Sep 2015
Deputy Manager
Hcl Technologies Jul 2008 - Jul 2009
Senior Analyst
Education:
Kurukshetra University, Kurukshetra 2002 - 2006
Bachelors, Computer Engineering
Skills:
Project Managment, Risk Management, Infrastructure, Iis, Reporting, Web Servers, Market Research, Application Servers, Itil, Monitoring, Team Management, Windows Server, Project Management, Active Directory, Business Analysis, Vendor Management, Management, Requirements Analysis, Pre Sales, Sql, Crm, It Service Management, Microsoft Sql Server, Service Delivery
Sarabjot Singh Photo 35

Sarabjot Singh

Sarabjot Singh Photo 36

Sarabjot Singh

Sarabjot Singh Photo 37

Sarabjot Singh

Sarabjot Singh Photo 38

Sarabjot Singh

Publications & IP owners

Us Patents

Method And Apparatus For Determining Tag Location

US Patent:
2015024, Sep 3, 2015
Filed:
Feb 28, 2014
Appl. No.:
14/193867
Inventors:
- Murray Hill NJ, US
- Paris FR, US
Irwin Kennedy - Londonerry, IE
Stefan Valentin - Stuttgart, DE
Dmitry Chizhik - Highland Park NJ, US
Gregory Wright - Fair Haven NJ, US
Sarabjot Singh - Austin TX, US
Assignee:
Alcatel-Lucent USA Inc. - Murray Hill NJ
Alcatel Lucent - Paris
International Classification:
G01S 5/02
Abstract:
Various embodiments provide a method and apparatus for determining tag location by using one or more estimated channel responses (CR) that characterize the wireless channel between the tag and one or more respective anchors. In particular, a tracking server in communication with the anchor(s) determines the tag's location based on a comparison of the estimated CR(s) with a set of stored CRs associated with the anchor(s).

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