The 276th R-CCS Cafe (Jan 14, 2025) | RIKEN Center for Computational Science RIKEN Website

TOP Events & Outreach R-CCS Cafe The 276th R-CCS Cafe (Jan 14, 2025)

Details
Date	Tue, Jan 14, 2025
Time	3:00 pm - 5:00 pm (3:00 pm - 4:15 pm Talks and Discussions, 4:15 pm - 5:00 pm Free discussion and coffee break)
City	Kobe, Japan/Online
Place	Lecture Hall (6th floor) at R-CCS, Online seminar on Zoom If you are not affiliated with R-CCS and would like to attend R-CCS Cafe, please email us at r-ccs-cafe[at]ml.riken.jp.
Language	Presentation Language: English Presentation Material: English
Speakers	Hirozumi Yamaguchi Large-Scale Digital Twin Research Team Team Leader Hirofumi Tomita Computational Climate Science Research Team Team Leader Keiji Yamamoto Advanced Operation Technologies Unit Unit Leader

Talk Titles and Abstracts

1st Speaker: Hirozumi Yamaguchi

Title:
Large-scale digital twin for Society5.0
Abstract:
The large-scale digital twin research team is developing advanced digital twin platforms that integrate cyber-physical systems with Fugaku. These platforms span diverse application domains, including smart environments that sense and replicate human behavior in cyberspace, smart buildings optimized for comfortable movement, and urban transportation systems where human and vehicle flows are managed, incorporating 5G/6G communication for safe autonomous driving. For disaster scenarios, we explore how ICT can support effective evacuation during hazardous events. Our recent focus extends to space, leveraging collaboration among multiple LEO satellites to deliver communication and sensing services to Earth. These efforts address key challenges in smart cities and align with Society 5.0's vision for a super-smart society, driving advancements in traffic management, disaster resilience, environmental sustainability, and smart infrastructure.

2nd Speaker: Hirofumi Tomita

Title:
Recent activities in Computational Climate Study Research Team
Abstract:
One of the missions of our team is to provide an open-source library for weather and climate models. It is not only for the models themselves but also for the data analysis routines. In recent years, the use of AI for weather forecasting and climate prediction has seen significant advancements. However, it is important to note that the input for these AI models depends on the preciseness of physical models. Unfortunately, weather and climate physical models are still incomplete and have uncertainties. Improving the accuracy of training data is essential for the further development of AI-based weather and climate models. This presentation will particularly focus on a new physics-based dynamical core developed by our team. We will discuss its aim and advantages, addressing the future challenges associated with it.

3rd Speaker: Keiji Yamamoto

Title:
TBD
Abstract:
TBD

Important Notes

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（Jan 7, 2025）