HomeAutomotiveToyota Research Institute has selected their AI research team

Toyota Research Institute has selected their AI research team

The Toyota Research Institute (TRI) today announced the hiring of its technical leadership team, bringing together an all-star group of scientists and engineers to help drive research into artificial intelligence and robots. TRI CEO Gill Pratt introduced the technical team and initial TRI research programs in a press conference at the 2016 International Consumer Electronics Show. In addition to the technical team, TRI work will be guided by an Advisory Board of corporate, scientific and public policy leaders from around the world.

Toyota MIT Stanford AI

First announced in November 2015, TRI is a research and development enterprise designed to bridge the gap between fundamental research and product development. Funded by an initial five-year, $1 billion investment, it has been launched with mandates to enhance the safety of automobiles, with the ultimate goal of creating a car that is incapable of causing a crash; increase access to cars to those who otherwise cannot drive, including the handicapped and the elderly; help translate outdoor mobility technology into products for indoor mobility; and accelerate scientific discovery by applying techniques from artificial intelligence and machine learning.

Toyota MIT Stanford AI

The initial technical team includes:

  • Eric Krotkov, Former DARPA Program Manager – Chief Operating Officer
  • Larry Jackel, Former Bell Labs Department Head and DARPA Program Manager –  Machine Learning
  • James Kuffner, CMU Professor and former head of Google Robotics – Cloud Computing
  • John Leonard, Samuel C. Collins Professor of Mechanical and Ocean Engineering, MIT –  Autonomous Driving
  • Hiroshi Okajima, Project General Manager, R&D Management Division, Toyota Motor Corporation – Executive Liaison Officer
  • Brian Storey, Professor of Mechanical Engineering, Olin College of Engineering –  Accelerating Scientific Discovery
  • Russ Tedrake, Associate Professor in the Department of Electrical Engineering and Computer Science, MIT – Simulation and Control

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Daniel Sherman Fernandez
Daniel Sherman Fernandez
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