Search

Michael K Kinoti

from Oakland, CA
Age ~42
Get Report
Also known as:
Michael Kiogora Kinoti, Mike Kinoti, Michael Knoti
Connected to:
Takahiro Kinoto, 49Kayla J Kinowski, 27Marcus Kinpred, 52Kinross L Kinross, 53William C Kinross, 44Vanessa S Kinsala, 47Charles L Kinsall, 93Jordan Kinsall, 38Sander M Kinsall, 59Brett S Kinsaul, 61

Michael Kinoti Phones & Addresses

  • Oakland, CA
  • Seattle, WA
  • 22 University Blvd, Melbourne, FL 32901 (321) 768-0459
  • 220 University Blvd, Melbourne, FL 32901 (321) 768-0459
  • Mayfield Heights, OH
  • 2717 Western Ave APT 232, Seattle, WA 98121

Resumes

Resumes

Michael Kinoti Photo 1

Engineering Leader

View page
Location:
San Francisco, CA
Industry:
Computer Software
Work:
Uber
Senior Engineering Manager
Uber Dec 2016 - Dec 2018
Engineering Manager
Microsoft Sep 2015 - Nov 2016
Senior Software Engineering Manager
Microsoft Sep 2012 - Sep 2014
Senior Software Development Engineer Lead
Microsoft Feb 2006 - Sep 2011
Software Design Engineer and Software Engineer Ii
Education:
Harvard University 2017 - 2018
Florida Institute of Technology 2002 - 2005
Bachelors, Bachelor of Science, Software Engineering Strathmore College 2001 - 2002
Skills:
Software Development
Software Design
Software Engineering
C#
Data Mining
Distributed Systems
Agile Methodologies
Object Oriented Design
Algorithms
Testing
Multithreading
Sql
Scalability
Web Services
Git
Machine Learning
Search
Xml
Big Data
Languages:
Swahili
Michael Kinoti Photo 2

Michael Kinoti

View page

Publications

Us Patents

User Analysis Through User Log Feature Extraction

View page
US Patent:
20120278354, Nov 1, 2012
Filed:
Apr 29, 2011
Appl. No.:
13/097277
Inventors:
Shengquan Yan - Issaquah WA, US
Zhenghao Wang - Redmond WA, US
Xiao Huang - Seattle WA, US
Yu Chen - Sammamish WA, US
An Yan - Sammamish WA, US
Jeffrey Eric Larsson - Kirkland WA, US
Michael Kiogora Kinoti - Seattle WA, US
Peng Yu - Bellevue WA, US
Zijian Zheng - Bellevue WA, US
Assignee:
MICROSOFT CORPORATION - Redmond WA
International Classification:
G06F 17/30
US Classification:
707769, 707E17014
Abstract:
Systems, methods, and computer media for efficiently processing user log data are provided. A received user log data analysis request specifies: target user log features that identify users in a target user group, analysis user log features that identify data associated with the users in the target user group, and an analysis to perform on the identified data associated with the users in the target user group. Occurrences of specified features are extracted from user logs and stored. Users associated with an occurrence of each of the extracted and stored target user log features are identified as users in the target user group. Occurrences of the analysis user log features that are associated with a user in the target user group are extracted and reformatted for the analysis specified in the analysis request.

Stream Processing In Search Data Pipelines

View page
US Patent:
20200293536, Sep 17, 2020
Filed:
Mar 12, 2020
Appl. No.:
16/816882
Inventors:
- Redmond WA, US
Michael Kinoti - Seattle WA, US
Shengquan Yan - Issaquah WA, US
Peng Yu - Bellevue WA, US
Xian Zhang - Bellevue WA, US
Guixi Zou - Bellevue WA, US
Yin He - Kirkland WA, US
Xavier Drudis Rius - Bellevue WA, US
Miriam Rosenberg - Kirkland WA, US
Zijian Zheng - Bellevue WA, US
Assignee:
Microsoft Technology Licensing, LLC - Redmond WA
International Classification:
G06F 16/2455
Abstract:
Architecture that decomposes of one or more monolithic data concepts into atomic concepts and related atomic concept dependencies, and provides streaming data processing that processes individual or separate (atomic) data concepts and defined atomic dependencies. The architecture can comprise data-driven data processing that enables the plug-in of new data concepts with minimal effort. Efficient processing of the data concepts is enabled by streaming only required data concepts and corresponding dependencies and enablement of the seamless configuration of data processing between stream processing systems and batch processing systems as a result of data concept decomposition. Incremental and non-incremental metric processing enables realtime access and monitoring of operational parameters and queries.

Stream Processing In Search Data Pipelines

View page
US Patent:
20160224632, Aug 4, 2016
Filed:
Feb 2, 2015
Appl. No.:
14/612126
Inventors:
- Redmond WA, US
Michael Kinoti - Seattle WA, US
Shengquan Yan - Issaquah WA, US
Peng Yu - Bellevue WA, US
Xian Zhang - Bellevue WA, US
Guixi Zou - Bellevue WA, US
Yin He - Kirkland WA, US
Xavier Drudis Rius - Bellevue WA, US
Miriam Rosenberg - Kirkland WA, US
Zijian Zheng - Bellevue WA, US
Assignee:
Microsoft Corporation - Redmond WA
International Classification:
G06F 17/30
Abstract:
Architecture that decomposes of one or more monolithic data concepts into atomic concepts and related atomic concept dependencies, and provides streaming data processing that processes individual or separate (atomic) data concepts and defined atomic dependencies. The architecture can comprise data-driven data processing that enables the plug-in of new data concepts with minimal effort. Efficient processing of the data concepts is enabled by streaming only required data concepts and corresponding dependencies and enablement of the seamless configuration of data processing between stream processing systems and batch processing systems as a result of data concept decomposition. Incremental and non-incremental metric processing enables realtime access and monitoring of operational parameters and queries.
Control profile
Michael K Kinoti from Oakland, CA, age ~42 Get Report