Paul Suganthan

Paul Suganthan

I am a Software Engineer at Google Research since March 2018, working as a part of the Google Brain team to solve problems at the intersection of data management and machine learning (ML). Specifically, I am one of the core contributors of TensorFlow Data Validation, which is an open-source library that helps developers understand, validate, and monitor their ML data at scale.

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Authored Publications
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    Google
Validating Data and Models in Continuous ML pipelines
Evan Rosen
Gene Huang
Mike Dreves
Neoklis Polyzotis
Paul Suganthan
Zhuo Peng
IEEE TCDE (2021)
TensorFlow Data Validation: Data Analysis and Validation in Continuous ML Pipelines
Emily Caveness
Marty Zinkevich
Neoklis Polyzotis
Paul Suganthan
Sudip Roy
Zhuo Peng
SIGMOD (2020) (to appear)
From Data to Models and Back
Evan Rosen
Gene Huang
Mike Dreves
Neoklis Polyzotis
Paul Suganthan
Zhuo Peng
ACM
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