Biography
Dr. Yajie Zou has a solid background in the fields of freeway operation and intelligent transportation systems. His major research achievements are formulation and development of innovative statistical methods (e.g., copula-based modeling frameworks for generating microscopic traffic variables, latent class models for analyzing heterogeneous traffic data) that allow people to better understand the characteristics of freeway operations, and to better analyze highway accident data. Dr. Yajie Zou has worked extensively with the application and improvement of finite mixture models, multivariate modeling approaches, multivariate time series techniques, generalized linear and nonlinear regression models in transportation engineering. These research results have been widely used by transportation researchers.
Dr. Yajie Zou led or participated in several research projects in freeway operation and transportation safety. He served as Principal Investigator of the two projects: New Methodologies for Analyzing Freeway Traffic Flow Characteristics, which was funded by Southwest Region University Transportation Center; Developing a clustering-based empirical Bayes analysis method for hotspot identification, which was funded by The Pacific Northwest Transportation Consortium. He was also the major participants of Highway Grade Characterization and Operating Efficiency Methods, Tools and Data Development (funding source: Federal Highway Administration); Pilot Testing of SHRP 2 Reliability Data and Analytical Products (funding source: Strategic Highway Research Program); Digital Roadway Interactive Visualization and Evaluation Network (funding source: Washington State Department of Transportation); Study on Illumination for State Highways (funding source: Washington State Department of Transportation); and the Evaluation and Development of Pavement Scores, Performance Models and Needs Estimates (founding source: Texas Department of Transportation).
Dr. Yajie Zou’s research accomplishments have led to the publication of 20 papers in peer-reviewed journals and 17 papers at international conferences with a peer-reviewed process. The article “Analyzing different functional forms of the varying weight parameter for finite mixture of negative binomial regression models” is among the top-5-most-cited articles published in the journal Analytic Methods in Accident Research since 2014. Dr. Zou also received several important awards, such as the Transportation Research Board 2015 Young Researcher Award (TRB Committee ANB20) and the 2008 Department Head Fellowship from Texas A&M University. Besides, his academic accomplishments are widely recognized by the freeway operation and transportation safety research communities, and he served as the reviewer for the journals of Transportmetrica A: Transport Science, Journal of Transportation Engineering, Transportation Research - Part C, Transportation Research Record and Analytic Methods in Accident Research.
Education
Ph.D. Transportation Engineering, Texas A&M University (U.S.)
M.E. Transportation Engineering, Texas A&M University (U.S.)
B.E. Engineering Mechanics, Tongji University
Experience
Associate Professor, Tongji University
Research Associate, University of Washington (U.S.) Mar. 2014 – Aug. 2015
Visiting Scientist, University of Washington (U.S.) Oct. 2013 – Feb. 2014
Research interests
Freeway operations
Intelligent transportation systems
Traffic safety
Applications of statistical analysis in transportation
Honors & Awards
Transportation Research Board (TRB Committee ANB20) 2015 Young Researcher Paper Award
Top 5 most cited articles published in Analytic Methods in Accident Research since 2014
Department Head Fellowship, Zachry Department of Civil Engineering, Texas A&M University, College Station, 2008.
Publications
1. Zou, Y., Zhang, Y., 2015. A copula-based approach to accommodate the dependence among microscopic traffic variables., Accepted by Transportation Research Part C. (SCI)
2. Zou, Y., Henrickson K., Lord, D., Wang, Y., and Xu K., 2015. Application of finite mixture models for analyzing freeway incident clearance time. Accepted by Transportmetrica A: Transport Science. (SCI)
3. Zou, Y., Hua, X., Zhang, Y., Wang, Y., 2015. Hybrid short-term freeway speed prediction methods based on periodic analysis. Canadian Journal of Civil Engineering, 42 (8), 570-582. (SCI)
4. Zou, Y., Wu, L., Lord, D., 2015. Modeling over-dispersed crash data with a long tail: examining the accuracy of the dispersion parameter in negative binomial models. Analytic Methods in Accident Research, 5, 1-16.
5. Zou, Y., Kristian, H., Wu, L., Wang, Y., Zhang, Z., 2015. Application of the Empirical Bayes method with the finite mixture model for identifying accident-prone spots. Accepted by Mathematical Problems in Engineering. (SCI)
6. Zou, Y., Zhu, X., Zhang, Y., Zeng, X., 2014. A space-time diurnal method for short-term freeway travel time prediction. Transportation Research Part C, 43(1), 33-49. (SCI)
7. Zou, Y., Zhang, Y., Zhu, X., 2014. Constructing a bivariate distribution for freeway speed and headway data. Transportmetrica A: Transport Science, 10(3), 255-272. (SCI)
8. Zou, Y., Zhang, Y., Lord, D., 2014. Analyzing different functional forms of the varying weight parameter for finite mixture of negative binomial regression models. Analytic Methods in Accident Research, 1, 39-52. (Top 6 most cited articles published in Analytic Methods in Accident Research since 2014)
9. Zou, Y., Lord, D., Zhang, Y., Peng, Y., 2014. Application of the Bayesian model averaging in predicting motor vehicle crashes. Journal of transportation and statistics,10(1), 49-60.
10. Zou, Y., Lord, D., Zhang, Y., Peng, Y., 2013. Comparison of Sichel and Negative Binomial models in estimating empirical bayes estimates. Transportation Research Record, 2392, 11-21. (SCI)
11. Zou, Y., Zhang, Y., Lord, D., 2013. Application of finite mixture of negative binomial regression models with varying weight parameters for vehicle crash data analysis. Accident Analysis & Prevention, 50, 1042-1051. (SSCI)
12. Zou, Y., Zhang, Y., 2011. Use of skew-normal and skew-t distributions for mixture modeling of freeway speed data. Transportation Research Record, 2260, 67-75. (SCI)
Education
Ph.D. Transportation Engineering, Texas A&M University (U.S.)
M.E. Transportation Engineering, Texas A&M University (U.S.)
B.E. Engineering Mechanics, Tongji University
Experience
Associate Professor, Tongji University
Research Associate, University of Washington (U.S.) Mar. 2014 – Aug. 2015
Visiting Scientist, University of Washington (U.S.) Oct. 2013 – Feb. 2014
Research interests
Freeway operations
Intelligent transportation systems
Traffic safety
Applications of statistical analysis in transportation
Honors & Awards
Transportation Research Board (TRB Committee ANB20) 2015 Young Researcher Paper Award
Top 5 most cited articles published in Analytic Methods in Accident Research since 2014
Department Head Fellowship, Zachry Department of Civil Engineering, Texas A&M University, College Station, 2008.
Publications
1. Zou, Y., Zhang, Y., 2015. A copula-based approach to accommodate the dependence among microscopic traffic variables., Accepted by Transportation Research Part C. (SCI)
2. Zou, Y., Henrickson K., Lord, D., Wang, Y., and Xu K., 2015. Application of finite mixture models for analyzing freeway incident clearance time. Accepted by Transportmetrica A: Transport Science. (SCI)
3. Zou, Y., Hua, X., Zhang, Y., Wang, Y., 2015. Hybrid short-term freeway speed prediction methods based on periodic analysis. Canadian Journal of Civil Engineering, 42 (8), 570-582. (SCI)
4. Zou, Y., Wu, L., Lord, D., 2015. Modeling over-dispersed crash data with a long tail: examining the accuracy of the dispersion parameter in negative binomial models. Analytic Methods in Accident Research, 5, 1-16.
5. Zou, Y., Kristian, H., Wu, L., Wang, Y., Zhang, Z., 2015. Application of the Empirical Bayes method with the finite mixture model for identifying accident-prone spots. Accepted by Mathematical Problems in Engineering. (SCI)
6. Zou, Y., Zhu, X., Zhang, Y., Zeng, X., 2014. A space-time diurnal method for short-term freeway travel time prediction. Transportation Research Part C, 43(1), 33-49. (SCI)
7. Zou, Y., Zhang, Y., Zhu, X., 2014. Constructing a bivariate distribution for freeway speed and headway data. Transportmetrica A: Transport Science, 10(3), 255-272. (SCI)
8. Zou, Y., Zhang, Y., Lord, D., 2014. Analyzing different functional forms of the varying weight parameter for finite mixture of negative binomial regression models. Analytic Methods in Accident Research, 1, 39-52. (Top 6 most cited articles published in Analytic Methods in Accident Research since 2014)
9. Zou, Y., Lord, D., Zhang, Y., Peng, Y., 2014. Application of the Bayesian model averaging in predicting motor vehicle crashes. Journal of transportation and statistics,10(1), 49-60.
10. Zou, Y., Lord, D., Zhang, Y., Peng, Y., 2013. Comparison of Sichel and Negative Binomial models in estimating empirical bayes estimates. Transportation Research Record, 2392, 11-21. (SCI)
11. Zou, Y., Zhang, Y., Lord, D., 2013. Application of finite mixture of negative binomial regression models with varying weight parameters for vehicle crash data analysis. Accident Analysis & Prevention, 50, 1042-1051. (SSCI)
12. Zou, Y., Zhang, Y., 2011. Use of skew-normal and skew-t distributions for mixture modeling of freeway speed data. Transportation Research Record, 2260, 67-75. (SCI)
Research interests
Freeway operations
Intelligent transportation systems
Traffic safety
Applications of statistical analysis in transportation
Honors & Awards
Transportation Research Board (TRB Committee ANB20) 2015 Young Researcher Paper Award
Top 5 most cited articles published in Analytic Methods in Accident Research since 2014
Department Head Fellowship, Zachry Department of Civil Engineering, Texas A&M University, College Station, 2008.
Publications
1. Zou, Y., Zhang, Y., 2015. A copula-based approach to accommodate the dependence among microscopic traffic variables., Accepted by Transportation Research Part C. (SCI)
2. Zou, Y., Henrickson K., Lord, D., Wang, Y., and Xu K., 2015. Application of finite mixture models for analyzing freeway incident clearance time. Accepted by Transportmetrica A: Transport Science. (SCI)
3. Zou, Y., Hua, X., Zhang, Y., Wang, Y., 2015. Hybrid short-term freeway speed prediction methods based on periodic analysis. Canadian Journal of Civil Engineering, 42 (8), 570-582. (SCI)
4. Zou, Y., Wu, L., Lord, D., 2015. Modeling over-dispersed crash data with a long tail: examining the accuracy of the dispersion parameter in negative binomial models. Analytic Methods in Accident Research, 5, 1-16.
5. Zou, Y., Kristian, H., Wu, L., Wang, Y., Zhang, Z., 2015. Application of the Empirical Bayes method with the finite mixture model for identifying accident-prone spots. Accepted by Mathematical Problems in Engineering. (SCI)
6. Zou, Y., Zhu, X., Zhang, Y., Zeng, X., 2014. A space-time diurnal method for short-term freeway travel time prediction. Transportation Research Part C, 43(1), 33-49. (SCI)
7. Zou, Y., Zhang, Y., Zhu, X., 2014. Constructing a bivariate distribution for freeway speed and headway data. Transportmetrica A: Transport Science, 10(3), 255-272. (SCI)
8. Zou, Y., Zhang, Y., Lord, D., 2014. Analyzing different functional forms of the varying weight parameter for finite mixture of negative binomial regression models. Analytic Methods in Accident Research, 1, 39-52. (Top 6 most cited articles published in Analytic Methods in Accident Research since 2014)
9. Zou, Y., Lord, D., Zhang, Y., Peng, Y., 2014. Application of the Bayesian model averaging in predicting motor vehicle crashes. Journal of transportation and statistics,10(1), 49-60.
10. Zou, Y., Lord, D., Zhang, Y., Peng, Y., 2013. Comparison of Sichel and Negative Binomial models in estimating empirical bayes estimates. Transportation Research Record, 2392, 11-21. (SCI)
11. Zou, Y., Zhang, Y., Lord, D., 2013. Application of finite mixture of negative binomial regression models with varying weight parameters for vehicle crash data analysis. Accident Analysis & Prevention, 50, 1042-1051. (SSCI)
12. Zou, Y., Zhang, Y., 2011. Use of skew-normal and skew-t distributions for mixture modeling of freeway speed data. Transportation Research Record, 2260, 67-75. (SCI)