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.
Machine-learning-assisted discovery of polymers with high thermal conductivity using a molecular design algorithm
2019355 citationsStephen Wu, Masa‐aki Kakimoto et al.npj Computational Materialsprofile →
Predicting Materials Properties with Little Data Using Shotgun Transfer Learning
2019282 citationsH. Yamada, Stephen Wu 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 Stephen 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 Stephen Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen Wu more than expected).
This network shows the impact of papers produced by Stephen 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 Stephen Wu. The network helps show where Stephen Wu may publish in the future.
Co-authorship network of co-authors of Stephen Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Stephen Wu.
A scholar is included among the top collaborators of Stephen 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 Stephen Wu. Stephen Wu is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Wu, Stephen, Masa‐aki Kakimoto, Bin Yang, et al.. (2019). Machine-learning-assisted discovery of polymers with high thermal conductivity using a molecular design algorithm. npj Computational Materials. 5(1).355 indexed citations breakdown →
10.
Lipková, Jana, Panagiotis Angelikopoulos, Stephen Wu, et al.. (2018). Personalized Radiotherapy Planning for Glioma Using Multimodal Bayesian Model Calibration.. arXiv (Cornell University).1 indexed citations
Huang, Yaoxian & Stephen Wu. (2014). Sensitivity of Global Wildfire Occurrences to Various Factors in the Context of Global Change. AGU Fall Meeting Abstracts. 2014.1 indexed citations
13.
Bertiger, Willy, Y. Bar-Sever, Srinivas Bettadpur, et al.. (2002). GRACE: millimeters and microns in orbit. Proceedings of the 15th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 2002). 2022–2029.42 indexed citations
14.
Haines, Bruce, et al.. (1993). A review of GPS-based tracking techniques for TDRS orbit determination. Telecommunications and Data Acquisition Progress Report. 115. 1–16.1 indexed citations
15.
Wu, Stephen, et al.. (1990). Minimizing selective availability error on Topex GPS measurements. 606–611.10 indexed citations
16.
Yunck, T. P., et al.. (1987). Precise Near-Earth Navigation With GPS: A Survey of Techniques. Telecommunications and Data Acquisition Progress Report. 91. 29–45.1 indexed citations
17.
Yunck, T. P., Stephen Wu, & S. M. Lichten. (1985). A GPS measurement system for precise satellite tracking and geodesy. The Journal of the Astronautical Sciences. 33.9 indexed citations
18.
Wu, Stephen, et al.. (1982). Orbit determination of low-altitude earth satellites using GPS RF Doppler. 85–91.1 indexed citations
19.
Wu, Stephen. (1979). Connection and validation of narrow-band delta VLBI phase observations. 13–20.
20.
Wu, Stephen. (1978). Frequency selection and calibration of a water vapor radiometer. 43. 67–81.3 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.