As an associate professor jointly appointed in Georgia Tech’s School of Interactive Computing and School of City & Regional Planning, Andris relies on government data for her research, so slowdowns like this can be more than inconvenient. They can also hinder scientific discovery.
The problem is that many government websites that host the data aren’t user-friendly. These data sources are complex and voluminous, and the search engines are inefficient at narrowing down what users are seeking.
“It kind of has a ‘last mile’ problem,” Andris said. “Government workers and geospatial data workers have spent so much time and money creating these data sources. They’ve kept such great records year after year, but then that last mile is, how do we get it to people?”
Andris advised the federal government on this challenge while serving on the National Geospatial Advisory Committee (NGAC). The committee was formed by the Department of the Interior under the Geospatial Data Act of 2018, which established a new system for how the federal government collects, manages, and shares geospatial data.
Andris rotated off the committee in 2025 but led a report released in March 2026 titled Improving the Digital Experience for Users of National Geospatial Data. In the report, Andris and her collaborators outline recommendations for making geospatial data easy to retrieve and download.
These recommendations were intended for government agencies with websites that feature maps and segment data by geographic region. These agencies included the U.S. Census Bureau, the United States Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the Environmental Protection Agency (EPA), and NASA.
“The NGAC hadn’t focused yet on the way that users are interfacing with these sites, but it’s in our best interest to study it,” Andris said.
Andris and her co-authors on the report focused on five key areas for improvement:
One glaring crack in the system Andris found was the frequency with which drop-down menus didn’t immediately take the user to the data or let them download it.
“When users click on something that says data, they should be able to get data,” she said. “It’s like going to a vending machine and having it ask if you’d like to learn more about vending machines instead of giving you what you want.”
Andris said users should also be able to know as much as possible about a file before downloading it.
“People are used to seeing reviews and ratings on sites like Amazon to get a sense of how many people are using a product,” she said. “In that respect, we think people should be given more metrics on how many downloads the data they are seeking has.
“They should be able to see the metadata—including the file size so they can know how much space it will take up before downloading. They should also know the file type and whether they can open it in their software.”
Andris said there’s wisdom in emulating how private companies design their websites.
“Retail sites have conditioned people to expect things to be easy. They get what they want in one click. If they don’t find what they’re looking for almost immediately, they might give up. Adopting some of these practices from industry would probably be a good idea.”
For more information about the NGAC, visit https://www.fgdc.gov/ngac/. For the full report written by Andris, click here.
]]>As an associate professor jointly appointed in Georgia Tech’s School of Interactive Computing and School of City & Regional Planning, Andris relies on government data for her research, so slowdowns like this can be more than inconvenient. They can also hinder scientific discovery.
]]>Wang is a recipient of the 2025 Outstanding Dissertation Award from the Association for Computing Machinery Special Interest Group on Computer-Human Interaction (ACM SIGCHI). The award recognizes Wang for his lifelong work on democratizing human-centered AI.
“Throughout my Ph.D. and industry internships, I observed a gap in existing research: there is a strong need for practical tools for applying human-centered approaches when designing AI systems,” said Wang, now a safety researcher at OpenAI.
“My work not only helps people understand AI and guide its behavior but also provides user-friendly tools that fit into existing workflows.”
[Related: Georgia Tech College of Computing Swarms to Yokohama, Japan, for CHI 2025]
Wang’s dissertation presented techniques in visual explanation and interactive guidance to align AI models with user knowledge and values. The work culminated from years of research, fellowship support, and internships.
Wang’s most influential projects formed the core of his dissertation. These included:
“I feel extremely honored and lucky to receive this award, and I am deeply grateful to many who have supported me along the way, including Polo, mentors, collaborators, and friends,” said Wang, who was advised by School of Computational Science and Engineering (CSE) Professor Polo Chau.
“This recognition also inspired me to continue striving to design and develop easy-to-use tools that help everyone to easily interact with AI systems.”
Like Wang, Chau advised Georgia Tech alumnus Fred Hohman (Ph.D. CSE 2020). Hohman won the ACM SIGCHI Outstanding Dissertation Award in 2022.
Chau’s group synthesizes machine learning (ML) and visualization techniques into scalable, interactive, and trustworthy tools. These tools increase understanding and interaction with large-scale data and ML models.
Chau is the associate director of corporate relations for the Machine Learning Center at Georgia Tech. Wang called the School of CSE his home unit while a student in the ML program under Chau.
Wang is one of five recipients of this year’s award to be presented at the 2025 Conference on Human Factors in Computing Systems (CHI 2025). The conference occurs April 25-May 1 in Yokohama, Japan.
SIGCHI is the world’s largest association of human-computer interaction professionals and practitioners. The group sponsors or co-sponsors 26 conferences, including CHI.
Wang’s outstanding dissertation award is the latest recognition of a career decorated with achievement.
Months after graduating from Georgia Tech, Forbes named Wang to its 30 Under 30 in Science for 2025 for his dissertation. Wang was one of 15 Yellow Jackets included in nine different 30 Under 30 lists and the only Georgia Tech-affiliated individual on the 30 Under 30 in Science list.
While a Georgia Tech student, Wang earned recognition from big names in business and technology. He received the Apple Scholars in AI/ML Ph.D. Fellowship in 2023 and was in the 2022 cohort of the J.P. Morgan AI Ph.D. Fellowships Program.
Along with the CHI award, Wang’s dissertation earned him awards this year at banquets across campus. The Georgia Tech chapter of Sigma Xi presented Wang with the Best Ph.D. Thesis Award. He also received the College of Computing’s Outstanding Dissertation Award.
“Georgia Tech attracts many great minds, and I’m glad that some, like Jay, chose to join our group,” Chau said. “It has been a joy to work alongside them and witness the many wonderful things they have accomplished, and with many more to come in their careers.”
]]>Wang is a recipient of the 2025 Outstanding Dissertation Award from the Association for Computing Machinery Special Interest Group on Computer-Human Interaction (ACM SIGCHI). The award recognizes Wang for his lifelong work on democratizing human-centered AI.
]]>