Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Dynamic network models and driver information systems
1991386 citationsMoshe Ben‐Akiva, Isam Kaysi et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Isam Kaysi'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 Isam Kaysi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Isam Kaysi more than expected).
This network shows the impact of papers produced by Isam Kaysi. 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 Isam Kaysi. The network helps show where Isam Kaysi may publish in the future.
Co-authorship network of co-authors of Isam Kaysi
This figure shows the co-authorship network connecting the top 25 collaborators of Isam Kaysi.
A scholar is included among the top collaborators of Isam Kaysi 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 Isam Kaysi. Isam Kaysi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Abou-Zeid, Maya, et al.. (2015). Forecasting Students’ Demand for Shared-Ride Taxi Service Using an Integrated Choice and Latent Variable Model. Transportation Research Board 94th Annual MeetingTransportation Research Board.1 indexed citations
Kaysi, Isam, et al.. (2013). Users’ Evaluation of Rail Systems in Mass Events. Transportation Research Record Journal of the Transportation Research Board. 2350(1). 111–118.24 indexed citations
8.
Abou-Zeid, Maya, et al.. (2011). Measuring Aggressive Driving Behavior Using a Driving Simulator: An Exploratory Study.21 indexed citations
9.
Kaysi, Isam, et al.. (2007). A GIS-Based Framework for Multi-Criteria Evaluation and Ranking of Transportation Corridor Alternatives. 11th World Conference on Transport ResearchWorld Conference on Transport Research Society.2 indexed citations
Kaysi, Isam, et al.. (1999). CHARACTERIZING TRAFFIC CONDITIONS IN URBAN NETWORKS WITH MINIMAL CONTROL: A CASE STUDY OF POST-WAR BEIRUT.1 indexed citations
16.
Kaysi, Isam, et al.. (1995). INCREMENTAL BUS ALLOCATION WITH COMPETING MASS TRANSIT SERVICES. Transportation Research Record Journal of the Transportation Research Board. 68–74.
17.
Polydoropoulou, Amalia, et al.. (1994). DESIGN OF AN INTEGRATED DATA COLLECTION PROGRAM TO SUPPORT MODELING OF USER RESPONSE TO ATIS SERVICES.6 indexed citations
18.
Polydoropoulou, Amalia, Moshe Ben‐Akiva, & Isam Kaysi. (1994). INFLUENCE OF TRAFFIC INFORMATION ON DRIVERS' ROUTE CHOICE BEHAVIOR. Transportation Research Record Journal of the Transportation Research Board.47 indexed citations
19.
Kaysi, Isam, Moshe Ben‐Akiva, & Haris N. Koutsopoulos. (1993). INTEGRATED APPROACH TO VEHICLE ROUTING AND CONGESTION PREDICTION FOR REAL-TIME DRIVER GUIDANCE. Transportation Research Record Journal of the Transportation Research Board. 66–74.81 indexed citations
20.
Kaysi, Isam & Nigel H. M. Wilson. (1990). SCHEDULING TRANSIT EXTRABOARD PERSONNEL. Transportation Research Record Journal of the Transportation Research Board.2 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.