Citations per year, relative to Annie S. Wu Annie S. Wu (= 1×)
peers
Luiza de Macedo Mourelle
Countries citing papers authored by Annie S. Wu
Since
Specialization
Citations
This map shows the geographic impact of Annie S. Wu'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 Annie S. Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Annie S. Wu more than expected).
This network shows the impact of papers produced by Annie S. Wu. 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 Annie S. Wu. The network helps show where Annie S. Wu may publish in the future.
Co-authorship network of co-authors of Annie S. Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Annie S. Wu.
A scholar is included among the top collaborators of Annie S. Wu 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 Annie S. Wu. Annie S. Wu is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Knauf, Rainer, et al.. (2020). Character Depth and Sentence Diversification in Automated Narrative Generation.. The Florida AI Research Society. 21–26.1 indexed citations
6.
Wu, Annie S., et al.. (2020). Effects of Response Threshold Distribution on Dynamic Division of Labor in Decentralized Swarms.. The Florida AI Research Society. 386–391.2 indexed citations
7.
Wu, Annie S., et al.. (2019). A Genetic Algorithm Approach to Predictive Modeling of Medicare Payments to Physical Therapists.. The Florida AI Research Society. 311–317.2 indexed citations
8.
Wu, Annie S., et al.. (2018). Inter-Agent Variation Improves Dynamic Decentralized Task Allocation.. Journal of International Crisis and Risk Communication Research. 366–369.2 indexed citations
9.
Wu, Annie S., et al.. (2018). Specialization versus Re-Specialization: Effects of Hebbian Learning in a Dynamic Environment.. Journal of International Crisis and Risk Communication Research. 354–359.5 indexed citations
10.
Wu, Annie S., et al.. (2017). Effects of Task Consideration Order on Decentralized Task Allocation Using Time-Variant Response Thresholds.. Journal of International Crisis and Risk Communication Research. 466–471.3 indexed citations
Wu, Annie S., et al.. (2012). The Effects of Inter-Agent Variation on Developing Stable and Robust Teams.. Journal of International Crisis and Risk Communication Research.1 indexed citations
13.
Wu, Annie S., et al.. (2006). Conflict resolution and a framework for collaborative interactive evolution. Journal of International Crisis and Risk Communication Research. 512–517.5 indexed citations
Wu, Annie S. & Iván Garibay. (2002). The Proportional Genetic Algorithm Representation. Genetic and Evolutionary Computation Conference. 703–703.1 indexed citations
17.
Wu, Annie S., et al.. (2002). A simple method for detecting domino convergence and identifying salient genes within a genetic algorithm. Genetic and Evolutionary Computation Conference. 594–601.1 indexed citations
18.
Wu, Annie S., Robert Lindsay, & Rick Riolo. (1997). Empirical Observations on the Roles of Crossover and Mutation.. 362–369.25 indexed citations
19.
Lindsay, Robert & Annie S. Wu. (1996). Testing the robustness of the genetic algorithm on the floating building block representation. National Conference on Artificial Intelligence. 793–798.2 indexed citations
20.
Wu, Annie S.. (1995). Non-coding DNA and floating building blocks for the genetic algorithm.. Deep Blue (University of Michigan).7 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.