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Matthew Johnson

Machine learning researcher

Matthew Johnson is a Senior Research Scientist at Google DeepMind, where he has been part of the Brain Team since September 2016. His work focuses on machine learning, particularly in the areas of graphical models and model-based reinforcement learning. He is known for composing neural networks with graphical models and exploring scalable inference methods in Bayesian time series models.23

Educational Background

  • Ph.D. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (MIT), where he studied under Professor Alan Willsky, focusing on Bayesian methods.
  • M.S. in Electrical Engineering and Computer Science from MIT.
  • B.S. in Electrical Engineering and Computer Sciences from the University of California, Berkeley.2

Career Path

Before joining Google, Johnson completed two postdoctoral fellowships at Harvard University, working in both the Neurobiology Department and the Intelligent Probabilistic Systems Group. His early career included a role as a quantitative analyst intern at D.E. Shaw & Co. and teaching assistant positions at UC Berkeley.23

Research Interests

Johnson's research interests include:

  • Machine Learning: Development of algorithms that integrate neural networks with probabilistic graphical models.
  • Reinforcement Learning: Focusing on model-based approaches that learn from visual inputs.
  • Applications of AI: He has contributed to various projects aimed at enhancing machine learning systems for real-world applications.34

His contributions to the field are recognized through numerous publications and citations, reflecting his influence in advancing machine learning technologies.12

Highlights

‪Matthew A Johnson‬ - ‪Google Scholar‬
‪Matthew Johnson‬ - ‪Google Scholar‬
Jan 1 · github.com
Matthew Johnson mattjj - GitHub
Matthew Johnson mattjj - GitHub

Related Questions

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Matthew Johnson
Matthew Johnson, photo 1
Matthew Johnson, photo 2
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Location

San Francisco, California