©2017-2019 BY DISASTER DATA SCIENCE LAB.

WELCOME TO THE DISASTER DATA SCIENCE LAB

We are a group of data scientists and trainees who research how to leverage data to help others before, during, and after disasters. Globally, frequency and intensity of disasters are rising. We tackle pressing and challenging problems of disaster research by collecting and analyzing data to suggest evidence-based remedies.

 

PARTICIPATORY STATISTICAL INFERENCE OF INTERDEPENDENT CRITICAL INFRASTRUCTURE RECOVERY TIMES

The project will innovate a new methodological framework, as well as software tools to support this framework, for estimating post-event interdependent critical infrastructure recovery times. The core of the framework is a participatory process for eliciting recovery estimates from topical experts.
Support: National Science Foundation (CMMI-1824681)

AUTOMATIC DAMAGE DETECTION ON POST-HURRICANE SATELLITE IMAGERY

The governing research question of the project is: Can a machine learning algorithm automatically annotate damages on post-hurricane satellite images? To answer the question, the project uses satellite imagery data on the Greater Houston area after Hurricane Harvey in 2017, and damage labels created by crowdsourcing. The left-hand side image shows crowdsourced labels (1: Flooded/Damaged; 2: Non-damaged) and the right-hand side image shows our algorithm's prediction. For more information, please see the project website, presentation videoslides, and GitHub repo.
Support: Data Science for Social Good Program of the eScience Institute

INVESTIGATING THE IMPACT OF PROLONGED POWER OUTAGE ON THOSE RELYING ON ELECTRICITY-DEPENDENT MEDICAL EQUIPMENT

This service-oriented project studies how Hurricane Maria impacted public health of rural communities in Puerto Rico after Hurricane Maria that caused prolonged power outage. This interdisciplinary collaboration is featured by the University of WashingtonThe New York Times and other media outlets.  (Image credit to NASA: Puerto Rico's nighttime lights before and after Hurricane Maria)
Support: Global Innovation Fund of the University of Washington

BUILDING BACK BETTER: INNOVATIVE METHODS TO MEASURE RESILIENCE

During the disaster recovery process, it is extremely challenging to continuously assess community health and well-being. Readily available data sources on community health and wellbeing during the disaster recovery period are essential to assessing community recovery of health and wellbeing and to building capacity for community resilience. This study aims to understand if and how data from personal health monitoring devices and apps, such as Fitbit and Strava, can be used to understand community resilience and inform recovery activities in the recovery period. This project is an interdisciplinary collaboration with the Collaborative on Extreme Event Resilience. (Image credit to Strava Global Heatmap: Santa Rosa's aggregated, public activities for 2017-2018)
Support: Population Health Initiative of the University of Washington

 

PEOPLE

 

Lab Director &
Assistant Professor

Ph.D. (2016) Industrial & Operations Engineering
University of Michigan

M.A. (2016) Statistics
University of Michigan

B.S. (2010) Physics & Management Science
KAIST, Korea  

Graduate Researcher
(2016/9 – Present)

Ph.D. Student (2016 - Present) 
Industrial & Systems Engineering
University of Washington

M.Sc. (2016) Statistics
University of Washington

B.S. (2014) Statistics
University of Iowa, Iowa City, IA

Graduate Researcher
(2017/9 – Present)

Ph.D. Student (2017 - Present) 
Industrial & Systems Engineering
University of Washington

M.Sc. (2016)
Financial Engineering
University of Illinois at Urbana Champaign, IL

B.Eng. (2011) Civil Engineering
Nanyang Technological University, Singapore

Graduate Researcher
(2018/9 – Present)

M.Sc. (exp. 2018)

Computational Linguistics
University of Washington

M.A. (2015) Public Policy
University of Virginia

Volunteer Data Scientist
(2018/1 – Present)

M.A. (2014)
International Studies

University of Washington

Undergraduate Researcher
(2017/10 – Present)

B.Sc. (exp. 2020)
Industrial & Systems Engineering

University of Washington

Undergraduate Researcher
(2017/10 – Present)

B.Sc. (exp. 2020)
Industrial & Systems Engineering

University of Washington

Undergraduate Researcher
(2018/1 – Present)

B.Sc. (exp. 2019) 
Statistics & Economics

University of Washington

Undergraduate Researcher
(2018/1 – Present)

B.Sc. (exp. 2019) 
Statistics & Economics

University of Washington

Undergraduate Researcher
(2018/1 – Present)

B.Sc. (exp. 2019) 
Statistics, Mathematics (Minor),
& Applied Mathematics (Minor)

University of Washington

Undergraduate Researcher
(2018/1 – Present)

B.Sc. (exp. 2019) 
Industrial & Systems Engineering

University of Washington

Undergraduate Researcher
(2018/1 – Present)

B.Sc. (exp. 2019) 
Applied & Computational Mathematical Sciences  

University of Washington

Undergraduate Researcher
(2018/1 – Present)

B.Sc. (exp. 2020) 
Industrial & Systems Engineering

University of Washington

Undergraduate Researcher
(2018/1 – Present)

B.Sc. (exp. 2020)
Industrial & Systems Engineering

University of Washington

AMY XU

Undergraduate Researcher
(2018/1 – Present)

B.Sc. (exp. 2021)
Computer Science

University of Washington

Undergraduate Researcher
(2018/1 – Present)

B.Sc. (exp. 2021)
Computer Science or Informatics (Intended)

University of Washington

Undergraduate Researcher
(2018/3 – Present)

B.Sc. (exp. 2020)

Statistics & Psychology

University of Washington

Undergraduate Researcher
(2018/6 – Present)

B.Sc. (exp. 2021)

Mechanical Engineering

University of Washington

Alumni:

  • Zach McCauley, M.Sc. in Industrial Engineering, Graduate Researcher (2018/1 – 2018/12).

  • Xuejiao Li, B.Sc. in Applied Physics & Applied Mathematics (Minor), Undergraduate Researcher (2018/1 - 2018/9).  

  • Megan Miyasaki, B.Sc. in Physics, Undergraduate Researcher (2018/1 - 2018/9).

  • Christine Dien,  B.Sc. in Bioengineering, Undergraduate Researcher (2018/1 - 2018/6).

  • Randy Christopher Wenan, B.Sc. (2018), Industrial & Systems Engineering,  Undergraduate Researcher (2018/1 - 2018/6).

  • Daniel Colina,  B.Sc. in Informatics, Undergraduate Researcher (2018/1 - 2018/4)

  • Winter Meng, B.Sc. in Applied Physics & Applied Math, Undergraduate Researcher (2018/1 - 2018/3).


Openings: If you would like to be considered for participating in our lab's research, please send Prof. Choe an email with your resume and (unofficial) transcript. Those from traditionally underrepresented groups in STEM (e.g., women and minorities) are particularly encouraged to get in touch.

News

  • 5/20/2019: Aman Ankit (undergraduate researcher) and his research appear in the UW ISE News.

  • 11/5/2018: Daniel Cao Quoc Dung (graduate researcher) wins the 3rd place in the INFORMS Poster Competition at the INFORMS Annual Meeting, Phoenix, AZ and appears in the UW ISE News

CONTACT US

Aerospace & Engineering Research Building (AERB), 141F, Seattle, WA 98105

Prof. Youngjun Choe <ychoe@uw.edu>