APRU-IRIDeS Multi-Hazards Virtual Summer School 2020 (Part III)
APRU-IRIDeS Multi-Hazards Virtual Summer School 2020 (Part III)

The APRU-IRIDeS Multi-Hazards Virtual Summer School 2020 is organized by the APRU Multi-Hazards Program and the International Research Institute of Disaster Science at Tohoku University. The event aims to share the experiences and lessons learned from the Great East Japan Earthquake and Tsunami (GEJET), learn from the experiences in disaster risk reduction (DRR) and risk management from various stakeholders, and understand the latest international disaster science research conducted by the researchers globally.

As the last session of a three-part series, this webinar will focus on the latest research in disaster science.

Date and Time

  • Tuesday, July 28 at 7 pm (San Francisco & Vancouver)/9 pm (Mexico City & Quito)
  • Wednesday, July 29 at 10 am (Hong Kong & Manila)/11 am (Tokyo & Seoul)
  • Duration: 2 hours
Speakers & Resources

Presentation slides

  • John Rundle, Distinguished Professor of Physics and Earth & Planetary Science, UC Davis
  • Benito M. Pacheco, Professor at the Institute of Civil Engineering, UP Diliman
  • Riyanti Djalante, Academic Programme Officer at United Nations University-Institute for the Advanced Study for Sustainability
  • [Moderator] Takako Izumi, Associate Professor of IRIDeS, Tohoku University and Director of APRU Multi-Hazards Program

Revisit the webinar on YouTube

Additional Information

  • ​This webinar is open to the public and will be recorded for those who cannot attend live.
  • Visit here for news, events and resources of the APRU Multi-Hazards Program.
  • A certificate of attendance will only be issued to those who participate in all three virtual summer school sessions.
  • The views, information, or opinions expressed during webinars are solely those of the individuals involved and do not necessarily represent those of Association of Pacific Rim Universities (“APRU”) and its employees. APRU is not responsible for and does not verify for accuracy of any of the information contained in the series.