Ruiting Lian

404 total citations
8 papers, 228 citations indexed

About

Ruiting Lian is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Cognitive Neuroscience. According to data from OpenAlex, Ruiting Lian has authored 8 papers receiving a total of 228 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 4 papers in Computational Theory and Mathematics and 2 papers in Cognitive Neuroscience. Recurrent topics in Ruiting Lian's work include AI-based Problem Solving and Planning (4 papers), Computability, Logic, AI Algorithms (4 papers) and Natural Language Processing Techniques (2 papers). Ruiting Lian is often cited by papers focused on AI-based Problem Solving and Planning (4 papers), Computability, Logic, AI Algorithms (4 papers) and Natural Language Processing Techniques (2 papers). Ruiting Lian collaborates with scholars based in China, Hong Kong and France. Ruiting Lian's co-authors include Ben Goertzel, Hugo de Garis, Itamar Arel, Shuo Chen, Linas Vepštas, Michael S. Ross, Fabrício Alves Barbosa da Silva, Shuo Chen, Cassio Pennachin and Dingjie Wang and has published in prestigious journals such as Neurocomputing, Communication in Statistics- Theory and Methods and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Ruiting Lian

8 papers receiving 202 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ruiting Lian China	6	114	103	67	33	31	8	228
Thomas Miconi United States	10	101 0.9×	121 1.2×	51 0.8×	12 0.4×	31 1.0×	17	253
David Gamez United Kingdom	10	68 0.6×	156 1.5×	44 0.7×	24 0.7×	20 0.6×	30	242
Christian Huyck United Kingdom	11	198 1.7×	139 1.3×	74 1.1×	8 0.2×	35 1.1×	53	340
Alexander S. Klyubin United Kingdom	5	117 1.0×	127 1.2×	15 0.2×	32 1.0×	5 0.2×	6	269
Dongsung Huh United States	5	99 0.9×	170 1.7×	85 1.3×	4 0.1×	25 0.8×	8	243
Nick Jakobi United Kingdom	3	148 1.3×	70 0.7×	28 0.4×	14 0.4×	11 0.4×	3	234
David I. Feinstein United States	3	188 1.6×	164 1.6×	52 0.8×	14 0.4×	31 1.0×	8	324
Benjamin Scellier Switzerland	4	128 1.1×	103 1.0×	117 1.7×	8 0.2×	21 0.7×	5	216
N Rochester United States	7	140 1.2×	127 1.2×	37 0.6×	46 1.4×	36 1.2×	10	357
Craig M. Vineyard United States	7	157 1.4×	95 0.9×	193 2.9×	8 0.2×	45 1.5×	35	295

Countries citing papers authored by Ruiting Lian

Since Specialization

Citations

This map shows the geographic impact of Ruiting Lian'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 Ruiting Lian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ruiting Lian more than expected).

Fields of papers citing papers by Ruiting Lian

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ruiting Lian. 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 Ruiting Lian. The network helps show where Ruiting Lian may publish in the future.

Co-authorship network of co-authors of Ruiting Lian

This figure shows the co-authorship network connecting the top 25 collaborators of Ruiting Lian. A scholar is included among the top collaborators of Ruiting Lian 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 Ruiting Lian. Ruiting Lian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Lian, Ruiting, Changle Zhou, & Ben Goertzel. (2019). The probabilistic support Kendall correlation and its transitivity properties. Communication in Statistics- Theory and Methods. 49(2). 485–499. 1 indexed citations

2.

Goertzel, Ben, et al.. (2013). The cogprime architecture for embodied Artificial General Intelligence. 9 indexed citations

3.

Goertzel, Ben, et al.. (2011). Cognitive Synergy between Procedural and Declarative Learning in the Control of Animated and Robotic Agents Using the OpenCogPrime AGI Architecture. Proceedings of the AAAI Conference on Artificial Intelligence. 25(1). 1436–1441. 2 indexed citations

4.

Goertzel, Ben, Ruiting Lian, Itamar Arel, Hugo de Garis, & Shuo Chen. (2010). A world survey of artificial brain projects, Part II: Biologically inspired cognitive architectures. Neurocomputing. 74(1-3). 30–49. 93 indexed citations

5.

Lian, Ruiting, et al.. (2010). Sentence generation for artificial brains: A glocal similarity-matching approach. Neurocomputing. 74(1-3). 95–103. 6 indexed citations

6.

Goertzel, Ben, Ruiting Lian, Itamar Arel, Hugo de Garis, & Shuo Chen. (2010). World survey of artificial brains, Part II: Biologically inspired cognitive architectures. 7 indexed citations

7.

Goertzel, Ben, Cassio Pennachin, Fabrício Alves Barbosa da Silva, et al.. (2010). A General Intelligence Oriented Architecture for Embodied Natural Language Processing. 6 indexed citations

8.

Garis, Hugo de, et al.. (2010). A world survey of artificial brain projects, Part I: Large-scale brain simulations. Neurocomputing. 74(1-3). 3–29. 104 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.

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