Piyawat Lertvittayakumjorn
Research Scientist at Google
Mountain View, California, United States
Summary
👤
Senior🎓
Top SchoolPiyawat Lertvittayakumjorn is a research scientist at Google with 11 years of experience bridging academic rigor and applied ML, holding a Ph.D. from Imperial College London where he worked on explainable AI, natural language processing, and machine argumentation. His work focuses on making AI more effective and trustworthy for real-world deployment, with past projects spanning human-AI collaboration, knowledge-graph repair, and AI-supported decision making in healthcare regulation. He has experience in both industry and academia, including research roles at Royal Holloway and a virtual internship at AWS on conversational AI. A strong foundations builder, he combines top-tier academic training (MSc with distinction) and high-achieving undergraduate performance with hands-on prototyping from web apps to stream outlier detection. Based in Mountain View, he pairs deep research expertise with practical engineering instincts that accelerate translating interpretability research into production-relevant systems.
11 years of coding experience
5 years of employment as a software developer
Master’s Degree with distinction, Computer Science (Machine Learning), Master’s Degree with distinction, Computer Science (Machine Learning) at Imperial College LondonBachelor’s Degree, Computer Engineering, 3.98, Bachelor’s Degree, Computer Engineering, 3.98 at Chulalongkorn University
English, Thai
Github Skills (18)
grasp10
google7
meta-learning7
interpretable-machine-learning7
natural-language-processing7
natural-language-understanding7
classification7
nlp7
theorem6
semantic6
convolutional-neural-networks6
bert5
tensorflow5
text-classification5
visual-recognition4
Programming languages (4)
Github contributions (5)
plkumjorn/GrASP
Feb 2021 - Aug 2022
An implementation of GrASP (Shnarch et. al., 2017)
Contributions:62 commits, 1 PR, 33 pushes in 1 year 6 months
grasp
plkumjorn/CNNAnalysis
Aug 2019 - Oct 2020
Codes for the EMNLP 2019 paper -- "Human-grounded Evaluations of Explanation Methods for Text Classification" by Piyawat Lertvittayakumjorn and Francesca Toni
Contributions:27 commits, 5 PRs, 16 pushes in 1 year 2 months
nlpevaluationsexplanationtext-classificationconvolutional-neural-networks
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