Skip Navigation

Transportation Data Science Seminar Series

March 4 - December 16, 2021

8:00 pm - 9:00 pm

Online via zoom

Scope and Goals: The dynamics of coupled environmental and human systems, and their complexities and connectivity across space and time poses daunting challenges to effective solutions to a variety of mobility and sustainable issues. Data-driven transportation analytics has facilitated the understanding of the dynamics of these systems and their interactions. Analytical advancements have also enabled rigorous analysis of big data available from sensors and citizens to develop effective and timely solutions to challenging urban transportation problems and for policy interventions. This series invites research that sheds light on the opportunities, challenges and solutions of using big mobility data for transportation science and smart cities.

Organization: The Transportation Data Science Seminar Series is sponsored by the Department of Landscape Architecture and Urban Planning, the Texas A&M Transportation Institute and the Texas A&M Institute of Data Science. Please contact Xinyue Ye (LAUP), Michael Martin (TTI), or Xiao Li (TTI) for further information.

Zoom Meeting ID: 732 641 0814 Passcode: 575829

Schedule: Seminars will usually take place bi-weekly, with variations to accommodate the academic calendar.

DateSpeakerAffiliationTitle
3/4/2021Michael MartinTexas A&M Transportation InstituteConnected Vehicle Data Safety Applications & Emerging Trends
3/11/2021Subasish DasTexas A&M Transportation InstituteApplication of Big Data in Highway Safety Modeling
4/1/2021Lingtao WuTexas A&M Transportation InstituteIntroduction on How to Estimate Transportation Safety
4/15/2021Pan XuNew Jersey Institute of Technology Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms
4/29/2021Hui KongUniversity of MinnesotaTransportation Network Companies and the Future of Urban Mobility
05/20/2021Bahar DadashovaTexas A&M Transportation InstituteRandom Parameter Models for Estimating Statewide Daily Bicycle
Counts using Crowdsourced Data
06/03/2021Kailai WangUniversity of HoustonGenerational Trends in Travel Mode Choice
06/17/2021Yu ZhangUniversity of South FloridaNetwork Design and Traffic Management of Urban Air Mobility
07/01/2021Yalong PiTexas A&M Institute of Data ScienceTraffic Information Retrieval and Analysis in Major Events Based on Monitoring Visual Data
07/15/2021Xilei ZhaoUniversity of FloridaPlanning Innovative Mobility Systems with Machine Learning
07/29/2021Tianjun LuCalifornia State University, Dominguez HillsLeveraging Data Science for Transportation and Environmental Challenges
08/12/2021Maryam MousaviTexas A&M Transportation InstituteSafety and Operational Benefits of Autonomous Vehicles on an Urban Arterial Nearby a Driveway
08/26/2021Jason WuTexas A&M Transportation InstituteBuilding a Smart Work Zone Using Roadside LiDAR
09/09/2021Soheil SohrabiTexas A&M Transportation InstituteHow to Evaluate Automated Vehicle Safety with Limited Data?
09/23/2021Yunlong ZhangTexas A&M Department of Civil & Environmental EngineeringUsing an Interpretable Machine Learning Framework to Understand Mobility and Reliability Considerations in Truck Drivers’ Route Choice
10/07/2021Xiaojiang LiTemple UniversityTBD
10/21/2021Wenwen ZhangRutgers UniversityTBD
11/04/2021Daoqing TongArizona State UniversityTBD
11/18/2021Ralph BuehlerVirginia TechTBD
12/02/2021Rebecca SandersSafe Streets Research & ConsultingTBD
12/16/2021Christopher CherryUniversity of TennesseeTBD