Lawrence Birnbaum

1.9k total citations
76 papers, 1.2k citations indexed

About

Lawrence Birnbaum is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Lawrence Birnbaum has authored 76 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 7 papers in Computer Networks and Communications. Recurrent topics in Lawrence Birnbaum's work include AI-based Problem Solving and Planning (15 papers), Semantic Web and Ontologies (12 papers) and Natural Language Processing Techniques (11 papers). Lawrence Birnbaum is often cited by papers focused on AI-based Problem Solving and Planning (15 papers), Semantic Web and Ontologies (12 papers) and Natural Language Processing Techniques (11 papers). Lawrence Birnbaum collaborates with scholars based in United States. Lawrence Birnbaum's co-authors include Gregg Collins, Roger C. Schank, Margot Flowers, Kristian J. Hammond, Frederick Hayes‐Roth, Earl D. Sacerdoti, John W. Benoit, Mark Stefik, Bruce Krulwich and Jay Budzik and has published in prestigious journals such as Molecular and Cellular Biology, Plastic & Reconstructive Surgery and Artificial Intelligence.

In The Last Decade

Lawrence Birnbaum

71 papers receiving 954 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lawrence Birnbaum United States 20 743 135 115 94 77 76 1.2k
Marco Colombetti Italy 20 906 1.2× 133 1.0× 67 0.6× 101 1.1× 90 1.2× 66 1.2k
Edwina L. Rissland United States 23 1.1k 1.4× 182 1.3× 61 0.5× 49 0.5× 65 0.8× 48 1.6k
Kathryn Merrick Australia 16 408 0.5× 68 0.5× 52 0.5× 92 1.0× 96 1.2× 60 810
Antonio M. Mora Spain 19 487 0.7× 135 1.0× 64 0.6× 97 1.0× 162 2.1× 113 1.1k
Christopher K. Riesbeck United States 13 379 0.5× 82 0.6× 107 0.9× 24 0.3× 41 0.5× 61 661
Michel C. Desmarais Canada 18 703 0.9× 369 2.7× 331 2.9× 66 0.7× 64 0.8× 88 1.4k
Keeley Crockett United Kingdom 18 1.2k 1.6× 373 2.8× 252 2.2× 86 0.9× 50 0.6× 111 1.7k
David Maulsby Canada 12 531 0.7× 320 2.4× 73 0.6× 219 2.3× 123 1.6× 31 1.2k
Anthony F. Norcio United States 14 226 0.3× 279 2.1× 62 0.5× 104 1.1× 43 0.6× 45 869
Jason C. Hung Taiwan 17 340 0.5× 149 1.1× 56 0.5× 206 2.2× 117 1.5× 117 966

Countries citing papers authored by Lawrence Birnbaum

Since Specialization
Citations

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

Fields of papers citing papers by Lawrence Birnbaum

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lawrence Birnbaum

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

All Works

20 of 20 papers shown
1.
Iacobelli, Francisco, et al.. (2010). Finding new information via robust entity detection. National Conference on Artificial Intelligence. 32–37. 4 indexed citations
2.
Liu, Jiahui, et al.. (2006). Using Explicit Semantic Models to Track Situations across News Articles. National Conference on Artificial Intelligence. 42–47. 6 indexed citations
3.
Birnbaum, Lawrence, et al.. (2005). Analogy, intelligent IR, and knowledge integration for intelligence analysis. National Conference on Artificial Intelligence. 32–37. 5 indexed citations
4.
Birnbaum, Lawrence. (2001). Addition of conjugated linoleic acid to a herbal anticellulite pill. Advances in Therapy. 18(5). 225–229. 5 indexed citations
5.
Brand, Matthew, et al.. (1993). Sensible scenes: visual understanding of complex structures through causal analysis. National Conference on Artificial Intelligence. 588–593. 12 indexed citations
6.
Brand, Matthew & Lawrence Birnbaum. (1992). Perception as a matter of design. National Conference on Artificial Intelligence. 5 indexed citations
7.
Birnbaum, Lawrence & Gregg Collins. (1991). Machine learning : proceedings of the Eighth International Workshop (ML91). 38 indexed citations
8.
Jona, Menachem Y., et al.. (1991). Using Button Theory to structure student-teacher interaction in computer-based learning environments. International Conference of Learning Sciences. 1 indexed citations
9.
Birnbaum, Lawrence & Gregg Collins. (1991). Proceedings of the eighth international workshop on Machine learning. Molecular and Cellular Biology. 8(10). 4257–69. 55 indexed citations
10.
Collins, Gregg, Lawrence Birnbaum, Bruce Krulwich, & Michael Freed. (1991). Plan debugging in an intentional system. International Joint Conference on Artificial Intelligence. 353–358. 8 indexed citations
11.
Krulwich, Bruce, Lawrence Birnbaum, & Gregg Collins. (1990). Goal-directed diagnosis of expectation failures. National Conference on Artificial Intelligence. 2 indexed citations
12.
Birnbaum, Lawrence, et al.. (1990). Problem-solver state descriptions as abstract indices for case retrieval. National Conference on Artificial Intelligence. 2 indexed citations
13.
Birnbaum, Lawrence, Gregg Collins, Michael Freed, & Bruce Krulwich. (1990). Model-based diagnosis of planning failures. National Conference on Artificial Intelligence. 318–323. 52 indexed citations
14.
Birnbaum, Lawrence. (1985). Lexical ambiguity as a touchstone for theories of language analysis. International Joint Conference on Artificial Intelligence. 815–820. 6 indexed citations
15.
Birnbaum, Lawrence. (1985). A short note on opportunistic planning and memory in arguments. International Joint Conference on Artificial Intelligence. 281–283. 4 indexed citations
16.
Birnbaum, Lawrence. (1982). Argument molecules: a functional representation of argument structure. National Conference on Artificial Intelligence. 62–65. 30 indexed citations
17.
Birnbaum, Lawrence, et al.. (1981). Opportunistic processing in arguments. International Joint Conference on Artificial Intelligence. 58–60. 22 indexed citations
18.
Birnbaum, Lawrence, et al.. (1980). Towards an AI model of argumentation. National Conference on Artificial Intelligence. 313–315. 32 indexed citations
19.
Schank, Roger C., Michael Lebowitz, & Lawrence Birnbaum. (1980). An integrated understander. Computational Linguistics. 6(1). 13–30. 51 indexed citations
20.
Schank, Roger C., Michael Lebowitz, & Lawrence Birnbaum. (1979). Parsing directly into knowledge structures. International Joint Conference on Artificial Intelligence. 772–777. 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.

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