Researcher Spotlight: Natalia Ruiz Juri
The Data Rodeo has a new head wrangler: Natalia Ruiz Juri is the new director of CTR’s Network Modeling Center (NMC). The NMC’s mission is to accelerate the impact of academic research in transportation practice via new data and technologies, creating partnerships between UT Austin and the private and public sectors. A CTR researcher since 2010, Dr. Ruiz Juri completed her undergraduate studies in Civil Engineering at the National University of Cordoba, in Argentina, and then joined the UT Austin civil engineering program as a Fulbright Scholar. After obtaining her Master’s degree working in integrated land-use and transportation issues, she earned her Ph.D. specializing in transportation network modeling.
NMC is home to the Data Rodeo, a concept that arose from NMC’s participation in Austin’s 2016 Smart City proposal. Dr. Ruiz Juri explains, “given the major role that data plays in transportation modeling and research, and the potential it holds to transform the way in which transportation systems are planned and operated, the NMC is striving to promote open access to and enable the use of traffic and related data through its web-based Data Rodeo initiative.” The Data Rodeo provides single-point access to data from multiple sources, and also access to different types of tools to work with such data that may be appropriate for a range of users. NMC partners with UT’s Texas Advanced Computing Center to corral the Data Rodeo, making use TACC’s heavy-duty servers.
It also allows the NMC to host events centered on open-access data, such as the ATX Hack the Traffic hackathon, through which data was shared with civic hackers in order to promote and guide innovative uses of data. While some users may be interested in simply downloading subsets of data or visualizing data availability, others may want to process very large data sets, map them to a network graph, or use them within algorithms or models. “In the long term,” Dr. Ruiz Juri says, “the Data Rodeo will enable a variety of research and modeling workflows that are expected to allow for a more efficient data use, promote replicable and transferable research, and enable students and researchers to work with real world data, and to build on the work of others when appropriate, focusing on innovation.”
The first step to make Data Rodeo a reality is to gain access to additional traffic data collected by the public and, potentially, the private sector. This requires understanding of not only what’s available, but also the existing technical and institutional challenges to sharing it, the corresponding access restrictions, and legal and privacy concerns. But, Dr. Ruiz Juri observes, “because the NMC has established relationships with a variety of state and local agencies and private-sector consultants, its researchers have a deep understanding of similarities in data collection and unique sharing challenges, and can identify and facilitate collaboration opportunities.”
Dr. Ruiz Juri’s own research includes the use of advanced network models in practice, the analysis of novel data sources to support modeling and other transportation applications such as innovative road weather management, and the analysis of new technologies such as connected and autonomous vehicles. She is the University of Texas Principal Investigator for ConnectSmart, an Advanced Transportation and Congestion Management Technology Deployment Program sponsored by the USDOT. ConnectSmart will build on NMC’s Data Rodeo concepts to facilitate ingesting, storing, analyzing, and sharing passively collected data. In the field of “smart” transportation, she is working with Bluetooth data from the City of Austin to develop a prototype web application to analyze travel times along corridors, visualizing typical variability of travel times throughout the day and across days and time periods.
Dr. Ruiz Juri brings an exceptional complement of research interests and expertise to lead the NMC into its next phase of growth, as it broadens its primary focus on transportation modeling to include the use of data, becoming an innovator and facilitator of data sharing, analysis, and applications in the future of smart transportation.