J. David Schaffer

9.1k total citations · 3 hit papers
52 papers, 4.6k citations indexed

About

J. David Schaffer is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Molecular Biology. According to data from OpenAlex, J. David Schaffer has authored 52 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 9 papers in Cognitive Neuroscience and 8 papers in Molecular Biology. Recurrent topics in J. David Schaffer's work include Evolutionary Algorithms and Applications (16 papers), Metaheuristic Optimization Algorithms Research (12 papers) and Neural Networks and Applications (10 papers). J. David Schaffer is often cited by papers focused on Evolutionary Algorithms and Applications (16 papers), Metaheuristic Optimization Algorithms Research (12 papers) and Neural Networks and Applications (10 papers). J. David Schaffer collaborates with scholars based in United States, Finland and Netherlands. J. David Schaffer's co-authors include Larry J. Eshelman, Richard A. Caruana, Rajarshi Das, Darrell Whitley, Keith E. Mathias, John J. Grefenstette, Stephen A. Zahorian, Walker H. Land, Paul R. Chiarot and Peter Huang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Neurophysiology and Scientific Reports.

In The Last Decade

J. David Schaffer

50 papers receiving 4.2k citations

Hit Papers

align trajectories

What are hit papers?

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.

Multiple Objective Optimization with Vector Evaluated Genetic Algorithms

1985 1.8k citations J. David Schaffer international conference on Genetic algorithms profile →
Proceedings of the third international conference on Genetic algorithms

1989 833 citations J. David Schaffer international conference on Genetic algorithms profile →
A study of control parameters affecting online performance of genetic algorithms for function optimization

1989 611 citations J. David Schaffer, Richard A. Caruana et al. international conference on Genetic algorithms profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
J. David Schaffer United States	18	2.6k	1.9k	532	525	351	52	4.6k
Marc Schoenauer France	27	2.4k 0.9×	1.6k 0.8×	417 0.8×	397 0.8×	462 1.3×	139	4.3k
Erik D. Goodman United States	37	3.1k 1.2×	2.0k 1.1×	485 0.9×	588 1.1×	427 1.2×	198	6.0k
Manuel Lozano Spain	38	4.3k 1.7×	2.3k 1.2×	700 1.3×	603 1.1×	516 1.5×	86	6.4k
Hans-Georg Beyer Austria	30	3.8k 1.5×	2.9k 1.5×	409 0.8×	656 1.2×	527 1.5×	120	6.6k
Michael Emmerich Netherlands	28	2.2k 0.9×	2.8k 1.5×	389 0.7×	429 0.8×	262 0.7×	172	4.6k
Konstantinos E. Parsopoulos Greece	29	2.7k 1.1×	1.6k 0.8×	335 0.6×	859 1.6×	786 2.2×	87	4.9k
Zhang Yon China	46	3.9k 1.5×	1.9k 1.0×	430 0.8×	848 1.6×	816 2.3×	352	7.5k
Kusum Deep India	35	3.1k 1.2×	1.6k 0.8×	618 1.2×	982 1.9×	972 2.8×	184	5.7k
Janez Brest Slovenia	30	4.7k 1.8×	3.0k 1.6×	312 0.6×	661 1.3×	733 2.1×	97	6.6k
Shahryar Rahnamayan Canada	33	4.8k 1.8×	2.8k 1.5×	503 0.9×	856 1.6×	800 2.3×	194	6.8k

Countries citing papers authored by J. David Schaffer

Since Specialization

Citations

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

Fields of papers citing papers by J. David Schaffer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J. David Schaffer. 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 J. David Schaffer. The network helps show where J. David Schaffer may publish in the future.

Co-authorship network of co-authors of J. David Schaffer

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

All Works

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20 of 20 papers shown

Schaffer, J. David, et al.. (2024). Electrospray deposition of physical unclonable functions for drug anti-counterfeiting. Scientific Reports. 14(1). 13256–13256. 3 indexed citations

Schaffer, J. David, et al.. (2017). Speech Processing Approach for Diagnosing Dementia in an Early Stage. 2705–2709. 23 indexed citations

Schaffer, J. David, et al.. (2016). Pulsations with reflected boundary waves: a hydrodynamic reverse transport mechanism for perivascular drainage in the brain. Journal of Mathematical Biology. 73(2). 469–490. 24 indexed citations

Mathur, Ravi, et al.. (2011). Evolutionary computation with noise perturbation and cluster analysis to discover biomarker sets. Procedia Computer Science. 6. 153–158. 2 indexed citations

Schaffer, J. David, et al.. (2002). Improving Digital Video Commercial Detectors With Genetic Algorithms. Genetic and Evolutionary Computation Conference. 1212–1218. 1 indexed citations

Mathias, Keith E., et al.. (2000). Code compaction using genetic algorithms. Genetic and Evolutionary Computation Conference. 710–717. 5 indexed citations

Eshelman, Larry J., Keith E. Mathias, & J. David Schaffer. (1997). Crossover Operator Biases: Exploiting the Population Distribution.. international conference on Genetic algorithms. 354–361. 53 indexed citations

Eshelman, Larry J. & J. David Schaffer. (1993). Crossover's Niche. international conference on Genetic algorithms. 9–14. 65 indexed citations

Schaffer, J. David & Larry J. Eshelman. (1993). Designing Multiplierless Digital Filters Using Genetic Algorithms. international conference on Genetic algorithms. 439–444. 17 indexed citations

10.

Whitley, L. Darrell & J. David Schaffer. (1992). COGANN-92 : International Workshop on Combinations of Genetic Algorithms and Neural Networks, June 6, 1992 Baltimore, Maryland. IEEE Computer Society Press eBooks. 2 indexed citations

11.

Schaffer, J. David, Richard A. Caruana, & Larry J. Eshelman. (1991). Using genetic search to exploit the emergent behavior of neural networks. MIT Press eBooks. 244–248. 5 indexed citations

12.

Schaffer, J. David & Larry J. Eshelman. (1991). On Crossover as an Evolutionarily Viable Strategy.. 61–68. 49 indexed citations

13.

Eshelman, Larry J. & J. David Schaffer. (1991). Preventing Premature Convergence in Genetic Algorithms by Preventing Incest.. international conference on Genetic algorithms. 12(7). 115–122. 179 indexed citations

14.

Schaffer, J. David, Richard A. Caruana, Larry J. Eshelman, & Rajarshi Das. (1989). A study of control parameters affecting online performance of genetic algorithms for function optimization. international conference on Genetic algorithms. 51–60. 611 indexed citations breakdown →

15.

Schaffer, J. David. (1989). Proceedings of the third international conference on Genetic algorithms. international conference on Genetic algorithms. 833 indexed citations breakdown →

16.

Eshelman, Larry J., Richard A. Caruana, & J. David Schaffer. (1989). Biases in the crossover landscape. international conference on Genetic algorithms. 10–19. 222 indexed citations

17.

Schaffer, J. David, et al.. (1987). An adaptive crossover distribution mechanism for genetic algorithms. international conference on Genetic algorithms. 32(1). 36–40. 128 indexed citations

18.

Schaffer, J. David & John J. Grefenstette. (1985). Multi-objective learning via genetic algorithms. International Joint Conference on Artificial Intelligence. 593–595. 56 indexed citations

19.

Schaffer, J. David. (1985). Learning Multiclass Pattern Discrimination. international conference on Genetic algorithms. 107(1-2). 74–79. 13 indexed citations

20.

Schaffer, J. David. (1985). Multiple Objective Optimization with Vector Evaluated Genetic Algorithms. international conference on Genetic algorithms. 93–100. 1807 indexed citations breakdown →

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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