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.
Robotics to promote elementary education pre-service teachers' STEM engagement, learning, and teaching
Countries citing papers authored by Prashant Doshi
Since
Specialization
Citations
This map shows the geographic impact of Prashant Doshi'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 Prashant Doshi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prashant Doshi more than expected).
This network shows the impact of papers produced by Prashant Doshi. 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 Prashant Doshi. The network helps show where Prashant Doshi may publish in the future.
Co-authorship network of co-authors of Prashant Doshi
This figure shows the co-authorship network connecting the top 25 collaborators of Prashant Doshi.
A scholar is included among the top collaborators of Prashant Doshi 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 Prashant Doshi. Prashant Doshi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Doshi, Prashant, et al.. (2019). Evacuate or Not? A POMDP Model of the Decision Making of Individuals in Hurricane Evacuation Zones.. Uncertainty in Artificial Intelligence. 669–678.2 indexed citations
Doshi, Prashant, et al.. (2009). Toward Integrating Social Trust into Web Service Compositions. National Conference on Artificial Intelligence. 65–66.1 indexed citations
13.
Rasheed, Khaled, et al.. (2008). Enhancing the Quality of Noisy Training Data Using a Genetic Algorithm and Prototype Selection.. International Conference on Artificial Intelligence. 821–827.5 indexed citations
14.
Doshi, Prashant, et al.. (2007). Regret-Based Decentralized Adaptation ofWeb Processes with Coordination Constraints.. 262–269.1 indexed citations
Doshi, Prashant & Piotr J. Gmytrasiewicz. (2005). A particle filtering based approach to approximating interactive POMDPs. National Conference on Artificial Intelligence. 969–974.15 indexed citations
Doshi, Prashant & Piotr J. Gmytrasiewicz. (2004). Towards Affect-based Approximations to Rational Planning: A Decision-Theoretic Perspective to Emotions. National Conference on Artificial Intelligence. 33–36.1 indexed citations
19.
Doshi, Prashant. (2004). A framework for optimal sequential planning in multiagent settings. National Conference on Artificial Intelligence. 985–986.2 indexed citations
20.
Doshi, Prashant, Lloyd Greenwald, & John R. Clarke. (2003). Using Bayesian Networks for Cleansing Trauma Data. The Florida AI Research Society. 72–76.3 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.