Tomas Pfister


Head of AI Research, Google Cloud

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Bio


Tomas Pfister is the Head of AI Research at Google Cloud where he leads efforts in inventing cutting-edge AI solutions to a wide range of real-world problems. He came to Google from Apple where he cofounded Apple's new central research group for Artificial Intelligence. He published Apple’s first research paper and won the Best Paper Award at CVPR, one of the most prestigious awards in AI. Tomas’ key scientific achievements have been proposing a method to improve the realism of synthetic images; developing the first automated method to detect facial micro-expressions; inventing a new way for neural networks to exploit spatiotemporal structure; one of the most accurate forecasting models for the COVID-19 pandemic; and state-of-the-art models for time series forecasting and tabular data prediction. His research has laid the foundation for several applications such as Face ID in iPhone X, autonomous driving, human pose estimation, detecting facial micro-expressions, translating sign language, document understanding, manufacturing defect detection, retail demand forecasting, and recommendation systems. Tomas did his PhD in deep learning with Prof Andrew Zisserman at Oxford University and bachelor’s degree in computer science at Cambridge University. He is the recipient of the Forbes 30 Under 30 award, and has received over 40 research awards, including 3 best paper awards, with numerous publications in top AI research venues. His work has been frequently featured in mainstream media, including Forbes, BusinessInsider & Wired [1] [2], as well as in Apple's inaugural Machine Learning Journal post.


News

2022

  • Now working primarily on LLMs in Google Cloud. We're hiring!
2020

  • Glad to announce the release of a significantly improved Google COVID-19 forecast that is now also available in Japan! More in the blog.
  • Excited to release the COVID-19 Public Forecasts in partnership with Harvard to help first responders and public officials track and predict future cases! Learn more in the blog, news ([1], [2], [3], [4]) and our paper.
  • Happy to announce that TabNet, a high-performance & explainable deep learning-based tabular learning model developed by Google Cloud researchers, is now available on the Google Cloud AI Platform! See more in blog post.
2019

  • Super excited to be working as Head of AI Research at Google Cloud with Andrew Moore to set up a new AI research group in Google! We're hiring!
2018 2017

Publications


CV