Shiro Yano

Shiro Yano

  • Large-scale traffic flow prediction
    Blackbox Optimization

He was engaged in basic and applied researches on reinforcement learning algorithms and black box optimization algorithms at the Universities (2007-2020).
Now, he is engaged in prediction techniques on large-scale traffic flow data and in blackbox optimization algorithms.

  • Department

    • Data Intelligence Platform Innovation Dept.,
      InfoTech Div.

  • Biography

    • 2020-

      Current position,
      Toyota-Otemachi, Infotech

    • 2015-
      2020

      Assistant Professor,
      Dept. of Computer and Information Science
      Tokyo University of Agriculture and Technology

    • 2012-
      2015

      Senior Researcher,
      Research organization of Science and Technology,
      Ritsumeikan University

    • 2007-
      2012

      Ph.D student,
      Dept. of Precision Engineering,
      The University of Tokyo

  • Publication List/Conference presentation

    Book

    • University of Tokyo press, ”Science of the Embodied brain systems and rehabilitations II”, 2019

    Conference presentation

    • "Keynote : Learning algorithms on cognitive science and behavioral science", Annual conference of the Robotics Society of Japan, 2019

    • "Tutorial on Blackbox optimization approach for reinforcement learning problems," Reinforcement learning workshop, The 12th Asian Control Conference 2019

    • "Mirror descent: Bridge between Bayesian-brain and Reinforcement learning algorithms," The 2018 Japan-America Frontiers of Engineering symposium (JAFOE 2018)

    Others

    • Tackling against the era of data localizations: Federated Learning Taskforce approaches, Woven by Toyota. Toyota Global Summit 2023

  • Commendation/Memberships

    • President of the young researchers' association "Embodied brain science" (2014-2019)

    • Committee member "SICE distributed autonomous systems committee" (2016-2018)

    • Best paper award, International conf. of Micro-Nano Mech. Human Science (2016)

Members List