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September 28, 2018, Filed Under: Uncategorized

CM2 Researcher Leading UT Austin’s Bridging Barriers Research Initiative

In 2016, UT Austin President Fenves introduced Bridging Barriers, a university-wide grand challenges initiative that brings together experts from across the 40 acres to address pressing problems facing Texas, the nation, and beyond. As the Bridging Barriers website explains, “The Office of the Vice President for Research invited the UT research community to submit concept papers describing creative ideas that could be shaped into large-scale, interdisciplinary grand challenge projects … These papers were then organized into six core themes.”

UTSOA Assistant Professor and CM2 researcher, Dr. Junfeng Jiao, is one of the leading Principal Investigators of the “Good Systems” theme, that explores how modern society’s complex web of technological systems — health care, transportation, government, communications, and artificial intelligence — can be made good for the wellbeing of individuals, and is determining what it will take to build future systems we can trust. 

Participants listen to the Grand Challenge Vision for the Good Systems theme

As one of the leaders of Good Systems, Dr. Jiao is working on three specific research initiatives:

  1. 311 Calls and 500 Cities Data Challenge: A one-day workshop leveraging data to capture how residents perceive the health of neighborhoods
  2. Leveraging Detailed Air Quality Data: Collaborative projects that leverage Google-car sampled air quality
  3. Future courses: Develop courses that can be used to apply and popularize the insights generated via Good Systems.
CM2 Researcher and Good Systems Leader Dr. Junfeng Jiao (left) with CM2 Director Dr. Ming Zhang (right)

On September 14th, the Bridging Barriers theme, Good Systems, held a Campus Engagement Workshop open to all interested faculty, staff, and students. Participants were invited to brainstorm and discuss the planning of development year research activities. CM2 Director, Dr. Ming Zhang also participated.

Following the presentations on the Mission, the Grand Vision Challenge, and the Planning for the Good Systems development year, participants formed break-out groups to discuss different projects based on their interest in Conceptual, Empirical, Technical, and Synthesis Investigations.

Dr. Jiao joined the Technical Investigations group to discuss his project on leveraging detailed air quality data from Google-cars in downtown Austin.  He explained that the project wants to use the live data from Google to see how pollution changes across time and space and then cross-reference that data with health data.

There are so many health conditions that are affected by air quality. Successful utilization of this very detailed, granular data could lead cities to find ways of collecting crowdsourced air quality data for more accurate, live monitoring. It could also be leveraged to get Google to collect more of this type of data for health research.

Dr. Jiao leads a breakout group on Leveraging Detailed Air Quality Data from Google cars

However, Dr. Jiao and his team don’t want to restrict themselves to just health concerns. As Dr. Bruce Porter from UT Austin’s Department of Computer Science pointed out, “there may be more subtle questions beyond health, so what can we do with this data that people will care about?” Ideally, the results of the study would identify unique sets of data that are useful for larger policy questions.

As Dr. Jiao concluded, “We need to think about how we use this data long-term, not just for Year-0 [of the Good Systems initiative].”

Dr. Jiao’s research focuses on using information technologies (GIS, GPS, Drone, smart phone, social media, wearable devices, etc.) to quantify built environments and understand its impact on people’s behavior (e.g. travel, physical, eating, etc.) and its health consequence. Currently, he has completed one research project under CM2 and has two other CM2 projects that are in progress. His CM2 project with Greg Griffin, “Can Crowdsourcing Support Co-productive Transportation Planning in Megaregion? Evidence from Local Practice” used crowdsourced data as an innovative method for public participation in transportation planning.

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