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Christian A. Sabillon

Graduate Research Assistant
University of Texas at Austin
Austin, TX, United States

Christian A. Sabillon is a graduate research assistant in the Department of Civil, Architectural and Environmental Engineering (CAEE) at The University of Texas at Austin, since 2019. Mr. Sabillon earned both his B.S. and M.S. degree in civil engineering from The University of Texas at Austin in 2019 and 2021, respectively. He is currently finishing a M.S. in Statistics and Data Science, as well as a Ph.D. in transportation engineering. Mr. Sabillon has doing research in the area of transportation engineering since 2017, when he undertook an undergraduate research position with Dr. Jorge Prozzi. Mr. Sabillon is experienced in database management, feature engineering, statistical analysis, and the application of machine learning and artificial intelligence models. He has two years of experience being a teaching assistant in undergraduate and graduate level engineering statistics courses, and one year of experience training a select group of undergraduate students on how to code and apply machine learning models. Mr. Sabillon’s field of expertise is pavement performance modelling, pavement design and management, and pavement surface properties. His recent work for the Texas Department of Transportation (TxDOT) includes project 0-7031, Towards Efficient Prediction of Highway Friction on an Annual Basis on Texas Network, where him along the research team developed an innovative way of prediction pavement friction using solely the pavement’s texture information. He has also aided in other TxDOT projects such as 0-6988, where developed of an algorithm that can determine when and where maintenance work is done on a roadway by looking solely at pavement distresses over time. Mr. Sabillon’s work is seen in 1 journal article, and three conference articles most of them revolving around the topic of pavement management, machine learning applications, and pavement surface properties. His most recent research project on friction prediction is currently patent pending.

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