Jingqin Gao

PhD Candidate, Research Assistant
  • jingqin.gao@nyu.edu
  • +1 646 997 3960
  • Short Bio

    Jingqin Gao is a Ph.D candidate at New York University Tandon school of Engineering. She studied Science and Technology of Optical Information and received her B.S. from Tongji University in China and her M.S in Transportation Planning and Engineering from New York University. Her research interests lie in offline and real-time simulation modeling, big data and machine learning approach for transportation, and transportation economics. She also worked for New York City Department of Transportation on modeling and data analysis to support the agency's internal planning, technical review processes and coordinated with external agencies on regional projects since 2012. Some of the key projects she involved included Manhattan Traffic Model, Off-Hour Deliveries, I-495 Managed Use Lane, Taxi GPS analysis, Regional traffic impact study for Newark Bay-Hudson County Extension bridge deck reconstruction, and Research on Concrete Applications for Sustainable Transportation (RE-CAST).

    Journal Papers

    1. Jingqin Gao, Kaan Ozbay, Hani N Nassif, Onur Kalan (2019), Stochastic Multi-Objective Optimization-Based Life Cycle Cost Analysis for New Construction Materials and Technologies, Transportation Research Record: Journal of the Transportation Research Board.
    2. Bekir Bartin, Kaan Ozbay, Jingqin Gao, Abdullah Kurkcu (2018), Calibration and validation of large-scale traffic simulation networks: a case study, Procedia Computer Science, Volume 130 Pages 844-849.
    3. Fan Zuo, Abdullah Kurkcu, Kaan Ozbay, Jingqin Gao (2018), Crowdsourcing Incident Information for Emergency Response Using Open Data Sources in Smart Cities, Transportation Research Record: Journal of the Transportation Research Board.
    4. Jingqin Gao, Kun Xie, Kaan Ozbay (2018), Exploring the Spatial Dependence and Selection Bias of Double Parking Citations Data, Journal of Transportation Research Record, (The Standing Committee on Urban Transportation Data and Information Systems (ABJ30)), DOI:10.1177/0361198118792323.

    Conference Papers

    1. Jingqin Gao, Kaan Ozbay, Fan Zuo, Abdullah Kurkcu (2018), A Life-Cycle Cost-Analysis Approach for Emerging Intelligent Transportation Systems with Connected and Autonomous Vehicles, Transportation Research Board 97th Annual Meeting, Washington DC, United States, January 7-11, 2018.
    2. Abdullah Kurkcu, Fan Zuo, Jingqin Gao, Ender Faruk Morgul, Kaan Ozbay (2017), Crowdsourcing Incident Information for Disaster Response Using Twitter, 96th TRB Annual Conference (CD-ROM), Washington, D.C., January, 2016. , (Standing Committee on Information Systems and Technology (ABJ50)).
    3. Jingqin Gao, Kaan Ozbay (2017), Data-Driven Approach to Estimate Double Parking Events Using Machine Learning Techniques, 96th TRB Annual Conference (CD-ROM), Washington, D.C., January, 2016. , (Standing Committee on Artificial Intelligence and Advanced Computing Applications (ABJ70)).
    4. Abdullah Kurkcu, Fan Zuo, Jingqin Gao, Kaan Ozbay (2017), Simulation Based Quantificaiton of the Potential Impacts of Incidents on Connected Vehicle Applications, INFORMS Transportation and Logistics Society First Triennial Conference Loyola University Chicago, USA 26-29 July 2017.
    5. Jingqin Gao, Kaan Ozbay (2016), Modeling Double-Parking Impact on Urban Streets , 95th TRB Annual Conference (CD-ROM), Washington, D.C., January, 2016. , (Transportation Demand Management (ABE50)).

    Invited Presentations or Posters

    1. Abdullah Kurkcu, Fan Zuo, Jingqin Gao, Ender Faruk Morgul (2016). Crowdsourcing Incident Information for Disaster Response Using Twitter . Transportation Technology Summit: Innovative Mobility Solutions. UTRC.
    2. Jingqin Gao, Kaan Ozbay (2016). Modeling and Predicting the Frequency and Impact of Double Parking Activities in Urban Area Using Big Data. Transportation Technology Summit: Innovative Mobility Solutions. UTRC.