Highlights:Developed predictive tools for PennDOT to forecast roadway safety performance, which improved the prediction accuracy by 2.7 to 37.2 percent for each road class comparing to the Highway Safety Manual methods. Conducted research on incorporating Bayesian methods into the propensity score matching framework. Improved the accuracy of safety treatment effect estimates by 9.6 percent. Introduced duration models to forecast pavement degradation and manage pavement maintenance for PA Turnpike.

Skills:Data Wrangling, SQL, Data Mining, python, R, Machine learning, General linear modeling

Goal:1. To be an expert in transportation and logistic optimization. 2. To be a consultant who provide data-driven and fact-based insights to influence business decision-making.

Certification:Stanford Machine Learning (Coursera), The Complete SQL Bootcamp (Udemy), Python Data Science and Machine learning Bootcamp (Udemy)

Honor:Finalist of Yale 4th Annual International Healthcare Case Competition. 2019 Nominated Top 5 team of Johns Hopkins University 8th Annual International Healthcare Case Competition by providing business development strategy for Next Healthcare Inc. 2018 ? Won the first place of TRB-ATSSA National Traffic Control Device Challenge two years in a row by designing autonomous vehicle guiding device and wrong-way driving signs. 2017, 2018 Best Presentation Award at Transportation Engineering and Safety Conference. (Top 2) 2016 Leo P. Russell Graduate Fellowship in Civil Engineering 2016

Traffic Engineer Intern 05/2017 - 08/2017
San Francisco International Airport, San Francisco, CA United States
Industry: Transportation, Aviation
Conduct survey, experimental study, data collection and policy investigation projects.
Alleviated terminal parking confliction by reconfiguring ground transportation parking zones, and edited and updated SFO parking regulations. Designed study, collected and analyzed pedestrian crossing data to validate the benefits of consolidating pedestrian crosswalk at terminals. Conducted a survey to investigate the impact of Uber/Lyft vehicles on airport ramp congestion.--
Research Assistant 05/2015 - 12/2018
Thomas D. Larson Pennsylvania Transportation Institute at Penn State, State College, PA United States
Industry: Transportation
Conduct data collection, data mining, statistical analysis, report drafting and project delivery to State Department of Transportation and Federal Highway Administration.
Developed predictive tools for PennDOT to forecast roadway safety performance, which improved the prediction accuracy by 2.7 to 37.2 percent for each road class comparing to the Highway Safety Manual methods. Built Pennsylvania roadway crash analytic database by integrating multiple data source using SQL and R. Identified the impact of socioeconomic status on travel demand using ordered and multinomial logit model. Conducted research on incorporating Bayesian methods into the propensity score matching framework. Improved the accuracy of safety treatment effect estimates by 9.6 percent. Assessed the effect of lowering posted speed limits and speed enforcement on reducing vehicle speed for the Montana DOT using linear and quantile models. Collected vehicle speed data and performed t-test, z-test and F-test to compare the performance of five dynamic curve warning system settings for Federal Highway Administration. Introduced duration models to forecast pavement degradation and manage pavement maintenance for PA Turnpike.--

Tongji University 09/2007 - 06/2011
Shanghai, Shanghai, China
Degree: Bachelor's Degree
Major:Civil Engineering
Study transportation design, pavement structure, and traffic safety risk mitigation, and designed driving fatigue detection system as thesis project.

Lingyu Li_Resume Analytics, Data mining, Consulting
Lingyu Li_CV Analytics, Data mining, Transportation consulting