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.
This map shows the geographic impact of Lipo Wang'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 Lipo Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lipo Wang more than expected).
This network shows the impact of papers produced by Lipo Wang. 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 Lipo Wang. The network helps show where Lipo Wang may publish in the future.
Co-authorship network of co-authors of Lipo Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Lipo Wang.
A scholar is included among the top collaborators of Lipo Wang 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 Lipo Wang. Lipo Wang is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Lan, Zirui, Olga Sourina, Lipo Wang, Reinhold Scherer, & Gernot Müller-Putz. (2017). Unsupervised Feature Learning for EEG-based Emotion Recognition. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 182–185.10 indexed citations
12.
Wang, Lipo, et al.. (2010). Stock Forecasting with Feedforward Neural Networks and Gradual Data Sub-Sampling. 11(4).40 indexed citations
13.
Jiao, Licheng, Lipo Wang, Xinbo Gao, Liu Jing, & Feng Wu. (2006). Advances in Natural Computation: Second International Conference, ICNC 2006, Xi'an, China, September 24-28, 2006, Proceedings, Part II (Lecture Notes in Computer Science). Springer eBooks.1 indexed citations
14.
Wang, Lipo & Xiuju Fu. (2005). Data Mining with Computational Intelligence (Advanced Information and Knowledge Processing). Springer eBooks.9 indexed citations
15.
Halgamuge, Saman & Lipo Wang. (2005). Classification and Clustering for Knowledge Discovery (Studies in Computational Intelligence). Springer eBooks.4 indexed citations
16.
Shi, Haixiang & Lipo Wang. (2005). Broadcast scheduling in wireless multihop networks using a neural-network-based hybrid algorithm. 18. 765–771.17 indexed citations
17.
Shi, Haixiang & Lipo Wang. (2003). A mixed branch-and-bound and neural network approach for the broadcast scheduling problem. 42–49.5 indexed citations
18.
Wang, Lipo, et al.. (2002). Cold rolling mill thickness control using the cascade-correlation neural network. Control and Cybernetics. 31(2). 327–342.4 indexed citations
Wang, Lipo & Daniel L. Alkon. (1993). Processing temporal sequences with a biologically-based artificial network. 331–334.1 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.