H. Gelernter

1.2k total citations
22 papers, 509 citations indexed

About

H. Gelernter is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Molecular Biology. According to data from OpenAlex, H. Gelernter has authored 22 papers receiving a total of 509 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 7 papers in Computational Theory and Mathematics and 3 papers in Molecular Biology. Recurrent topics in H. Gelernter's work include Logic, programming, and type systems (4 papers), AI-based Problem Solving and Planning (4 papers) and Computational Drug Discovery Methods (3 papers). H. Gelernter is often cited by papers focused on Logic, programming, and type systems (4 papers), AI-based Problem Solving and Planning (4 papers) and Computational Drug Discovery Methods (3 papers). H. Gelernter collaborates with scholars based in United States and Switzerland. H. Gelernter's co-authors include N Rochester, Josie Hansen, John R. Rose, Donald Loveland, David Larsen, Scott McN. Sieburth, John F. Tinker, D. A. Bromley, Ho‐Jane Shue and N. S. Sridharan and has published in prestigious journals such as Science, Biophysical Journal and Annals of the New York Academy of Sciences.

In The Last Decade

H. Gelernter

20 papers receiving 440 citations

Peers

H. Gelernter
Comparison fields: 5 of 90
  • Computational Theory and Mathematics 157
  • Artificial Intelligence 155
  • Molecular Biology 87
  • Materials Chemistry 72
  • Computer Networks and Communications 50
Replace Christian Merkwirth with:
Christian Merkwirth Germany
Minghu Song United States
Saurabh Srivastava India
Zois Boukouvalas United States
K. J. Harrison Australia
Neeraj Misra India
Dana Randall United States
Wayne Pullan Australia
Michael Albert New Zealand
Blake G. Fitch United States
Christian Merkwirth Germany View profile →
Citations per field, relative to H. Gelernter
H. Gelernter · 1×
Citations per year, relative to H. Gelernter
H. Gelernter · 1×

Countries citing papers authored by H. Gelernter

Since Specialization
Citations

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

Fields of papers citing papers by H. Gelernter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of H. Gelernter

This figure shows the co-authorship network connecting the top 25 collaborators of H. Gelernter. A scholar is included among the top collaborators of H. Gelernter 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 H. Gelernter. H. Gelernter 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
# Work Indexed citations
1 2
2 12
3
Realization of a geometry-theorem proving machine
36
4 11
5 0
6 7
7 20
8 87
9
A Heuristic Program to Discover Syntheses for Complex Organic Molecules.
1
10 3
11 25
12 85
13 10
14 1
15 40
16 40
17 14
18 3
19 51
20 3

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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