Transportation Data Science Seminar Series

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. This series is managed by Texas A&M Urban Data Science Lab.

Zoom Meeting ID: 732 641 0814 Passcode: 575829

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

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 UniversityUrban Streetscape and Human Movement Dynamics
10/21/2021Wenwen ZhangRutgers UniversityExploring the Impacts of Emerging Transportation Technologies Using Machine Learning Assisted Simulation
11/04/2021Daoqing TongArizona State UniversityThe Impact of COVID-19 on Food Access
11/18/2021Ralph Buehler John Pucher Virginia Tech
Rutgers University
Cycling for Sustainable Cities
12/02/2021Rebecca SandersSafe Streets Research & ConsultingInsights from a Multi-Pronged Exploration of Pedestrian Fatalities
12/16/2021Christopher CherryUniversity of TennesseeData Insights To Understand Micromobility User Behavior and Safety
2/3/2022Xiao HuangUniversity of ArkansasRevealing the disparity in human mobility dynamics during the COVID-19 pandemic via data-driven approaches
2/17/2022Harvey J. MillerOhio State UniversityMovement analytics for sustainable mobility: Using new geospatial and moving objects data to understand the environmental, social and economic performance of urban transportation
3/3/2022Joseph ChowNew York UniversityTackling operational inefficiencies toward sustainable Mobility-as-a-Service
3/24/2022Dominique LordTexas A&M Department of Civil & Environmental EngineeringApplication of Different Negative Binomial-Lindley Variations in Crash Data Modeling
3/31/2022Ruimin KeUniversity of Texas at El PasoReal-time video analytics empowered by machine learning and edge computing for smart transportation applications
4/14/2022Daniel PiatkowskiOslo Metropolitan UniversityWill We Ever Stop Driving? Aging, driving cessation, and auto-dependence in the US