I a postdoc fellow in CICS @ UMass Amherst starting from 2021 Fall.
I was selected as a Presidential Fellow at School of Data Science, and a Praxis Fellow of the Digital Humanities Fellows at UVA.
I also served as a graduate GIS technician at UVA's Scholars' Lab Spatial Tech group.
I received my Ph.D. in the Constructed Environment at University of Virginia (UVA), Master of Urban Planning from University at Buffalo, and B.Eng. degree in Urban and Regional Planning at Sichuan University.
My research is highly interdisciplinary and focuses on empowering AI and data-informed decision-making for social good. My research interests include a variety of topics about smart cities, including computational social science, human-computer interaction, urban big data mining and informatics, human mobility information retrieval with text mining, machine learning in travel behavior analysis.
GPA: 3.95/4
University of Virginia
GPA: 3.89/4
University at Buffalo, The State University of New York
GPA: 3.82/4
Sichuan University
deeplearning.ai
University of California San Diego
Stanford University
University of Illinois at Urbana-Champaign
New York University
Stanford University
University at Buffalo, The State University of New York
Double Hoo Research Grant. University Grant, 2018-2019, University of Virginia, Principle Investigator. Total amount: $9,000. Research project: Perceptions and Attitudes towards Driverless Shuttles: Integrating Social Media Data and Online Survey Data Presidential Fellowship in Data Science. Fellowship, 2018-2019, University of Virginia, Awardee. Total amount: $60,000 (tuition, health insurance and fees $30,000, fellowship grant $30,000). Research project: Evaluating air pollution exposure and environmental justice by integrating novel high-resolution nitrogen dioxide and human activity datasets Praxis Program Fellowship. Fellowship, 2018-2019, University of Virginia, Awardee. Total amount: $40,000 (tuition, health insurance and fees $30,000, fellowship grant $10,000). Research project: Unclosure: Exploring the Possibilities that the Public Domain holds for Research, Pedagogy, and Play. PhD in the Constructed Environment Research and Travel Grant. University Grant, 2018-2019, University of Virginia, Awardee. Total amount: $3,000. Research project: Geosocial Media and Travel Experience: A Text Mining Approach PhD in the Constructed Environment Research and Travel Grant. University Grant, 2017-2018, University of Virginia, Awardee. Total amount: $2,000. Research project: Parking Sentiment and the Supplies: A Sentiment Analysis of Online Reviews MATS UTC Research Grant (Mid-Atlantic Transportation Sustainability University Transportation Center). 2017, Graduate Research Student. Total amount: $45,338. Research project: Planning for Walking and Cycling in an Autonomous Vehicle Future PhD in the Constructed Environment Research and Travel Grant. University Grant, 2017, University of Virginia, Awardee. Total amount: $750. Research project: Examining Bikeability using GIS Modeling and CTPP (Census Transportation Planning Products) Data
Peer-reviewed Book chapter
Public Perceptions and Attitudes Towards Driverless Technologies in the United States: A Text Mining of Twitter Data
Zhiqiu Jiang, Max Zheng
Book Chapter for the CUPUM (Computational Urban Planning and Urban Management) Springer book 2021: "Urban Informatics and Future Cities". (2021). DOI: https://doi.org/10.1007/978-3-030-76059-5_7
Refereed Journal Articles
Acceptance of Driverless Shuttles in Pilot and Non-pilot Cities
Zhiqiu Jiang, Max Zheng, Andrew Mondschein
Journal of Public Transportation. (2021). (Accepted)
Analyzing Parking Sentiment and its Relationship to Parking Supply and the Built Environment using Online Reviews
Zhiqiu Jiang, Andrew Mondschein
Journal of Big Data Analytics in Transportation. (2021). DOI: https://doi.org/10.1007/s42421-021-00036-1
Synthesizing Neighborhood Preferences for Automated Vehicles
Wenwen Zhang, Kaidi Wang, Sicheng Wang, Zhiqiu Jiang, Andrew Mondschein, Robert Noland
Journal of Transportation Research Part C: Emerging Technologies. (2020). DOI: https://doi.org/10.1016/j.trc.2020.102774
Spatial Distributions of Attitudes and Preferences towards Autonomous Vehicles
Zhiqiu Jiang, Sicheng Wang, Andrew Mondschein, Robert Noland
Journal of Transport Findings. (2020). DOI: https://doi.org/10.32866/001c.12653
Attitudes towards Privately-Owned and Shared Autonomous Vehicles
Sicheng Wang, Zhiqiu Jiang, Robert Noland, Andrew Mondschein
Journal of Transportation Research Part F: Traffic Psychology and Behaviour. (2020). DOI: https://doi.org/10.1016/j.trf.2020.05.014
Using Social Media to Evaluate Associations between Parking Supply and Parking Sentiment
Andrew Mondschein, David King, Christopher Hoehne, Zhiqiu Jiang, and Mikhail Chester
Journal of Transportation Research Interdisciplinary Perspectives. (2020). DOI: https://doi.org/10.1016/j.trip.2019.100085
Examining the Effects of Proximity to Rail Transit on Travel to Non-Work Destinations: Evidence from Yelp Data for Cities in North America and Europe
Zhiqiu Jiang, Andrew Mondschein
Journal of Land Use and Transport. Vol. 12 No. 1 (2019). DOI: https://doi.org/10.5198/jtlu.2019.1409
Planning for Walking and Cycling in An Autonomous-Vehicle Future
Bryab Botello, Ralph Buehler, Steve Hankey, Andrew Mondschein, and Zhiqiu Jiang
Journal of Transportation Research Interdisciplinary Perspectives. Vol. 1, (2019). DOI: https://doi.org/10.1016/j.trip.2019.100012
Evaluating Fuel Tax Revenue Impacts of Electric Vehicle Adoption in Virginia Counties: Application of a Bivariate Linear Mixed Count Model
Wenjian Jia, Zhiqiu Jiang, Tong Donna Chen, and Rajesh Paleti
Transportation Research Record: Journal of the Transportation Research Board. Vol. 2673(9) 548–561, (2019). DOI: https://doi.org/10.1177/0361198119844973
A Psychological Approach to ‘Public Perception’of Land-Use Planning: A Case Study of Jiangsu Province, China
Zhongqiong Qu, Yiming Lu, Zhiqiu Jiang, Ellen Bassett, and Tao Tan
Sustainability. vol. 10(9) 1-20, (2018). DOI: https://doi.org/10.3390/su10093056
Peer Reviewed Conference Proceedings
Public Perceptions and Attitudes Towards Driverless Technologies in the United States: A Text Mining of Twitter Data
Zhiqiu Jiang, Max Zheng
Conference proceedings in the CUPUM (Computational Urban Planning and Urban Management) 2021 Conference: "Urban Informatics for Future Cities". (2021). DOI: https://doi.org/10.1007/978-3-030-76059-5_7
New Energy in Smart Mobility: Evaluating Fuel Tax Revenue Impacts of Electric Vehicle Adoption in Virginia Counties
Wenjian Jia, Zhiqiu Jiang, Tong Donna Chen, and Rajesh Paleti
Conference proceedings in International Conference on Transportation and Development 2019. (2019). DOI: https://doi.org/10.1061/9780784482582.009 Best Paper Award
University of Virginia
2020 Spring PLAN 2111 GIS for Planners
# of enrollment: 20
Undergraduate students from multiple departments (urban planning, architecture, engineering, political science, economics, sociology, etc.) across UVA
This course provides an introduction to geographic information systems (GIS) concepts and software.
In this course, I introduced the concepts of GIS as well as practical trainings on ESRI's ArcGIS suite and Open-source mapping, both in-person and online teaching.
My students successfully completed the course and obtained general familiarity with the major functionality of GIS and spatial data visualization.
University of Virginia
2018 Spring PLAN 6040 Quantitative Methods for Planners
Abstract: Increased travel as a result of urbanization and population growth has led to the need for safer, more efficient transportation in US cities. We examines whether the public believes driverless transportation systems could meet this demand by analyzing public social media data from Twitter. Using mined Twitter data (2012 - present), we conduct a two-pronged approach to understand public perceptions of driverless technology. We used a Natural Language Processing approach using topic modeling to infer latent topics of interest related to driverless technology, and developed a sentiment analysis model to uncover the public dominant emotions towards each area of interest. Through topic modeling, we uncovered a set of 5 latent themes consisting of Safety Perceptions, Technology Development, Industrial / System Integration, Milestone and Vision, and Ethics and Policy as well as their classified opinions of positive and negative. The findings indicate that safety, technological progress, and industrial and urban integration are of major concern that largely affect the public’s acceptance of driverless technology. Driverless vehicle developers can leverage these results to influence what functionalities they should improve upon, and how they can shape their marketing campaigns to cater to customers’ needs and expectations. More importantly, the findings will help public transport operators and city planners as they attempt to integrate autonomous vehicles into the urban transportation system.
Email: zj3av@virginia.edu
Website: https://zhiqiujiang.com