This map shows the geographic impact of Joshua Auld's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Joshua Auld with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joshua Auld more than expected).
This network shows the impact of papers produced by Joshua Auld. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Joshua Auld. The network helps show where Joshua Auld may publish in the future.
Co-authorship network of co-authors of Joshua Auld
This figure shows the co-authorship network connecting the top 25 collaborators of Joshua Auld.
A scholar is included among the top collaborators of Joshua Auld based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Joshua Auld. Joshua Auld is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Golshani, Nima, et al.. (2018). Modeling Evacuation Destination and Departure Time Choices for No-Notice Emergency Events. Transportation Research Board 97th Annual MeetingTransportation Research Board.1 indexed citations
8.
Auld, Joshua, et al.. (2018). Analyzing Intra-household Fully Autonomous Vehicle Sharing. Transportation Research Board 97th Annual MeetingTransportation Research Board.4 indexed citations
9.
Golshani, Nima, Ramin Shabanpour, Abolfazl Mohammadian, & Joshua Auld. (2017). Activity start time and duration: Incorporating hybrid utility-regret decision rules in joint models.2 indexed citations
10.
Shabanpour, Ramin, Nima Golshani, Joshua Auld, & Abolfazl Mohammadian. (2017). Willingness-to-pay for automated vehicles: A random parameters and random thresholds HOPIT model.5 indexed citations
11.
Shabanpour, Ramin, Nima Golshani, Joshua Auld, & Abolfazl Mohammadian. (2017). Dynamics of Time-of-Day Choices in Agent-Based Dynamic Activity Planning and Travel Simulation (ADAPTS) Framework. Transportation Research Board 96th Annual MeetingTransportation Research Board.1 indexed citations
12.
Auld, Joshua, Dominik Karbowski, Vadim Sokolov, & Nam Wook Kim. (2016). A Disaggregate Model System for Assessing the Energy Impact of Transportation at the Regional Level. Transportation Research Board 95th Annual MeetingTransportation Research Board.4 indexed citations
13.
Auld, Joshua, et al.. (2016). Addressing Some Issues of Map-Matching for Large-Scale, High-Frequency GPS Data Sets. Transportation Research Board 95th Annual MeetingTransportation Research Board.2 indexed citations
14.
Auld, Joshua, et al.. (2016). Long-Distance Trips and Mode Choice in Illinois. Transportation Research Board 95th Annual MeetingTransportation Research Board.3 indexed citations
Auld, Joshua, et al.. (2011). Senior Travelers' Trip Chaining Behavior: Survey Results and Data Analysis.1 indexed citations
18.
Auld, Joshua. (2011). Agent-based Dynamic Activity Planning and Travel Scheduling Model: Data Collection and Model Development.. Figshare.9 indexed citations
19.
Auld, Joshua, et al.. (2010). Evaluating Transportation Impacts of Forecast Demographic Scenarios Using Population Synthesis and Data Transferability. Transportation Research Board 89th Annual MeetingTransportation Research Board.5 indexed citations
20.
Auld, Joshua & Abolfazl Mohammadian. (2009). Adapts: Agent-Based Dynamic Activity Planning and Travel Scheduling Model--A Framework. Transportation Research Board 88th Annual MeetingTransportation Research Board.4 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.