vitae

General Information

Full Name Fei Sha
Contact me at feisha dot org

Education

  • 2007
    PhD
    University of Pennsylvania, Philadelphia, PA
    • Advisor: Prof. Lawrence K. Saul
    • PhD Thesis Committee: Prof. Fernando Pereira, Prof. Sam Roweis, Prof Mitch Marcus Prof. Dan Lee
    • Thesis: Large Margin Training of Acoustic Models for Speech Recognition

Academic Experience

  • 2021 - 2023
    Adjunct Professor
    University of Southern California, Los Angeles, CA, US
  • 2020 - 2021
    Professor
    University of Southern California, Los Angeles, CA, US
  • 2014 - 2020
    Associate Professor
    University of Southern California, Los Angeles, CA, US
  • 2016 - 2017
    Associate Professor
    University of California, Los Angeles, CA, US
  • 2008 - 2014
    Assistant Professor
    University of Southern California, Los Angeles, CA, US

Industry Experience

  • 2019 - now
    Research Scientist and Manager
    Google Research, Mountain View, CA
  • 2018 - 2019
    Director of Machine Learning
    Netflix Research, Los Gatos, CA
  • 2007 - 2008
    Research Scientist
    Yahoo! Research, Sunnyvale, CA

Honors and Awards

  • 2013
    • Alfred P. Sloan Research Fellowship
  • 2012
    • Army Research Office Young Investigator Award
  • 2006
    • Outstanding Student Paper, Neural Information Processing Systems (NIPS)
  • 2004
    • Outstanding Student Paper, Intl Conference on Machine Learning (ICML)

Academic Interests

  • Artificial Intelligence and Machine Learning
    • Probabilistic Models and Algorithms, Representation Learning
    • Natural Language Processing and Understanding, Knowledge Representation and Reasoning
    • Computer Vision, Multimodal Learning
  • AI for Science / Scientific Machine Learning
    • Turbulent Flow and Closure Modeling
    • Probabilistic Modeling and Inference for Physics-based Dynamical Systems
  • AI for Weather and Climate
    • Probabilistic Modeling in Weather Forecast and Climate Modeling
    • AI/ML Tools for Large-scale Weather and Climate Data Modeling and Analysis