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US-Japan Workshop: June 5 – 6 2017

1st US-Japan Workshop Enabling Global Collaborations in Big Data Research

J.W. Marriott Hotel, Buckhead, Atlanta, GA, USA June 5 – 6, 2017 


Workshop Objective

This workshop will bring together researchers from around the world to discuss experiences, challenges, and opportunities in transnational and international collaborative research on information technology (IT) and IT-supported applications, with focus on active collaborations between the United States (U.S.) and Japan. The workshop will provide opportunities for participants to interact directly and promote collaborative research activities. The collaboration is expected to achieve scientific knowledge that would be difficult to obtain individually.

Workshop attendance will be by invitation only, following response to this call as outlined below. Prospective attendees are expected to be investigators on funded research projects, and should submit papers or whitepaper for consideration by the program committee. Workshop organizers are requesting funding from NSF and JST to support partially the travel costs and registration fees of invited attendees from the U.S. and Japan. Principal Investigators of projects in relevant NSF and JST programs are strongly encouraged to apply. Additionally, early career researchers and underrepresented minorities are encouraged to apply.

Priority Research Topics

Topics of interest for collaboration include, but are not limited to:

  • Big Data Fundamental Technologies and Applications: novel techniques, methodologies, and technologies in computer science, statistics, computational science, and mathematics, together with innovative applications in domain science, which may include, for example, disaster management.
  • Smart and Connected Communities (SCC): strongly interdisciplinary, integrative research that will improve understanding of smart and connected communities and lead to discoveries that enable sustainable change to enhance community functioning.
  • Cyber-Physical Systems (CPS) and Internet of Things (IoT): system science needed to engineer complex, reliable cyber-physical systems that people can use, interact with, and depend upon, namely the cross-cutting fundamental scientific and engineering principles that underpin the integration of cyber and physical elements across all application sectors.
  • Artificial Intelligence and Machine Learning: research enabling computational understanding and modeling of intelligence in complex, realistic contexts, or more generally, processing and functionality to address data of unprecedented scale, complexity, heterogeneity, etc.



Please find the agenda here.

  US-Japan-workshop-agenda-v3.pdf (188.8 KiB, 199 hits)

White Papers

These whitepapers are being distributed for open access as part of the US-Japan Workshop, co-located with 2017 ICDCS, Atlanta, GA. For citations to work described in the whitepapers, please contact the authors.

  NSF-JST-whitepapers (29.6 MiB, 276 hits)


Regular Papers

These regular papers are a part of the 2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW) Proceedings.

  NSF-JST-regular papers (5.3 MiB, 300 hits)


Organizing Committee

Workshop Organizers

Calton Pu, Georgia Institute of Technology, USA

Masaru Kitsuregawa, University of Tokyo, Japan

Program Committee

Jose Fortes, University of Florida, USA

Etsuya Shibayama, University of Tokyo, Japan

Qingyang Wang, Louisiana State University, USA

April 2016 Kumamoto Earthquakes

There was a more powerful earthquake in Kumamoto at 01:25 on Saturday April 16, 2016, a day after an earlier tremor killed nine people.

Our tool collected the data about this event from social networks, such as Twitter, YouTube, and Instagram. The following videos, images, links, and events are from the data collected by the tool.



Oita – 2016-04-17
{“Twitter”: 5, “Total”: 5}
More Details
Tweet – “TwLandslide covers the main road connecting Oita and Kumamoto. Not helpful for Oita-based JSDF to aid in rescues.” –


Japan – 2016-04-16
{“Twitter”: 994, “Total”: 1047, “YouTube”: 4, “Instagram”: 3, “USGS”: 46}
More Details

#2016 #16 #april #earthquake #m7.3 #landslide #route57 #kumamoto #japan #prayforkumamoto

A photo posted by ryo (@granblue_61) on

Fast Moving Landslide



Minami Asomura – 2016-04-16
{“Twitter”: 78, “Total”: 78}
More Details
Tweet – “Landslide I tweeted about is in Minami Asomura. Another major aftershock M4.2 happened 7 min ago, but intensity not so big, but bad enough.”
south-aso – 2016-04-16
{“Twitter”: 7, “Total”: 7}
More Details
Tweet – “【BreakingNews】Following is reported: South-Aso bridge collapsed; massive widespread landslide at South-Aso Village #Kumamoto #earthquake”




Kyushu – 2016-04-14
{“Twitter”: 18, “Total”: 18}
More Details
Tweet – “RT @Durf: Warning from @torindol_ui: watch for rockfall in Kyushu’s mountainous areas.” -


Landslide blocks Batote – Kishtwar highway

Mar 13 2016

“The Batote- Kishtwar Highway, connecting twin districts of Doda and Kishtwar with rest of the state, was closed again on Sunday morning when a huge landslide blocked the road at Ragi-Nullah – 21 km from Doda.

After remaining closed for 18 hours due to landslide and shooting stones at half-a-dozen places, the road was opened for traffic yesterday afternoon.

Today morning, a massive landslide and a huge boulder blocked the road near Ragi-Nullah on Batote-Doda stretch.

More than 150 passenger vehicles and those carrying essential commodities were stranded on both sides of the highway.”

more information


Data produced by the system

db_id 6720
cell 2959_6138
score 0.478333333333
timestamp 2016-04-14 00:00:01
latitude 33.3115906
longitude 75.7662195
info {“Twitter”: 7, “Total”: 6}
details Detail

A new publication by GRAIT-DM team has been added

We added a new book chapter “Multi-hazard Detection by Integrating Social Media and Physical Sensors” developed by the GRAIT-DM team and published by Springer: see the Publications section of the portal.

Here is the abstract from the book chapter:
Disaster Management is one of the most important functions of the government. FEMA and CDC are two examples of government agencies directly charged with handling disasters, whereas USGS is a scientific agency oriented towards disaster research. But regardless of the type or purpose, each of the mentioned agencies utilizes Social Media as part of its activities. One of the uses of Social Media is in detection of disasters, such as earthquakes. But disasters may lead to other kinds of disasters, forming multi-hazards such as landslides. Effective detection and management of multi-hazards cannot rely only on one information source. In this chapter, we describe and evaluate a prototype implementation of a landslide detection system LITMUS, which combines multiple physical sensors and Social Media to handle the inherent varied origins and composition of multi-hazards. Our results demonstrate that LITMUS detects more landslides than the ones reported by an authoritative source.

Source code for LITMUS is released

We released the source code needed to run LITMUS experiments on Github: see The project contains ReadMe files that explain the overall flow of the project and provide details of the LITMUS components. We also added two sample files on landslides that should help users to get started. Please use the Contact page on this website if you need help or have comments.

On a recent landslide in Hiroshima, Japan

Landslide in Hiroshima, Japan

There was a recent major landslide in Hiroshima, Japan. Our tool available at collected the data from social networks about this event. The related data from Twitter, YouTube and Instagram is available here.

On a recent mudslide in Washington

Landslide in Washington

There was a recent major mudslide in Washington. Our tool available at collected the data from social networks about this event. The related data from Twitter, YouTube and Instagram is available here.

LITMUS: Landslide Detection by Integrating Multiple Sources

A new paper has been added to the Publications page: “LITMUS: Landslide Detection by Integrating Multiple Sources” by our team of Aibek Musaev, De Wang and Calton Pu. We will be presenting it at the ISCRAM conference later this year. In this paper, we evaluate a landslide detection system LITMUS, which combines multiple physical sensors and social media to handle the inherent varied origins and composition of multi-hazards. LITMUS integrates near real-time data from USGS seismic network, NASA TRMM rainfall network, Twitter, YouTube, and Instagram. The landslide detection process consists of several stages of social media filtering and integration with physical sensor data, with a final ranking of relevance by integrated signal strength.

List of Landslide Events by USGS

The US Geological Survey presents a continually updated list of news stories about recent landsldes around the world: There is also an archive of all news stories listed on one page:

The Landslide Blog on AGU Blogosphere

Dr. David Petley is the Wilson Professor of Hazard and Risk in the Department of Geography at Durham University in the United Kingdom. His blog provides a commentary on landslide events occurring worldwide, including the landslides themselves, latest research, and conferences and meetings: