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Doris S Xin

age ~33

from San Francisco, CA

Also known as:
  • Sui Yi Xin
  • Sui Y Xin
  • Suiyi Xin
  • Xin Doris
  • Xin Suiyi

Doris Xin Phones & Addresses

  • San Francisco, CA
  • Mountain View, CA
  • Berkeley, CA
  • Urbana, IL
  • Monrovia, CA
  • Champaign, IL
  • Arcadia, CA

Resumes

Doris Xin Photo 1

Research Intern

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Location:
1619 Josephine St, Berkeley, CA 94703
Industry:
Computer Software
Work:
Google May 2016 - Aug 2016
Research Intern

Google May 2015 - Aug 2015
Software Engineering Intern

University of Illinois at Urbana-Champaign May 2015 - Aug 2015
Research Assistant

Databricks May 2014 - Aug 2014
Software Engineering Intern

Linkedin Mar 2014 - May 2014
Senior Software Engineer
Education:
University of Illinois at Urbana - Champaign 2014 - 2019
Doctorates, Doctor of Philosophy, Computer Science
Caltech 2008 - 2012
Bachelors, Bachelor of Science, Computer Science
Skills:
Distributed Systems
Machine Learning
Java
Scala
Apache Spark
C++
Python
Hadoop
Apache Pig
Languages:
English
Doris Xin Photo 2

Doris Xin

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Us Patents

  • Holistic Optimization For Accelerating Iterative Machine Learning

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  • US Patent:
    20200184376, Jun 11, 2020
  • Filed:
    Dec 4, 2019
  • Appl. No.:
    16/702804
  • Inventors:
    - Urbana IL, US
    Stephen Macke - Urbana IL, US
    Doris Suiyi Xin - Urbana IL, US
  • International Classification:
    G06N 20/00
    G06F 11/34
    G06F 9/38
  • Abstract:
    A great deal of time and computational resources may be used when developing a machine learning or other data processing workflow. This can be related to the need to re-compute the workflow in response to adjustments to the workflow parameters, in order to assess the benefit of such adjustments so as to develop a workflow that satisfies accuracy or other constraints. Embodiments herein provide time and computational savings by selectively storing and re-loading intermediate results of steps of a data processing workflow. For each step of the workflow, during execution, a decision is made whether to store the intermediate results of the step. Thus, these embodiments can offer storage savings as well as processing speedups when repeatedly re-executing machine learning or other data processing workflows during workflow development.

Facebook

Doris Xin Photo 3

Doris Xin He

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Doris Xin Photo 4

Doris Xin

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Youtube

Doris Xin, CalTech

www.thephenomlis...

  • Category:
    People & Blogs
  • Uploaded:
    19 Dec, 2011
  • Duration:
    1m 42s

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