| 2023 | IJCNN | A Bio-Inspired Computational Astrocyte Model for Spiking Neural Networks. | Jacob Kiggins, J. David Schaffer, Cory E. Merkel |
| 2017 | Interspeech | Speech Processing Approach for Diagnosing Dementia in an Early Stage. | Roozbeh Sadeghian, J. David Schaffer, Stephen A. Zahorian |
| 2012 | GECCO | Evolving data sets to highlight the performance differences between machine learning classifiers. | Thomas Raway, J. David Schaffer, Kenneth J. Kurtz, Hiroki Sayama |
| 2010 | IJCNN | Evolving Spiking Neural Networks for predicting transcription factor binding sites. | Heike Sichtig, J. David Schaffer, Alberto Riva |
| 2009 | GECCO | A series of failed and partially successful fitness functions for evolving spiking neural networks. | J. David Schaffer, Heike Sichtig, Craig B. Laramee |
| 2008 | GECCO | SSNNS -: a suite of tools to explore spiking neural networks. | Heike Sichtig, J. David Schaffer, Craig B. Laramee |
| 2003 | CVPR | Envolvable Visual Commercial Detector. | Lalitha Agnihotri, Nevenka Dimitrova, Thomas McGee, Sylvie Jeannin, J. David Schaffer, Jan Nesvadba |
| 2002 | GECCO | Improving Digital Video Commercial Detectors With Genetic Algorithms. | J. David Schaffer, Lalitha Agnihotri, Nevenka Dimitrova, Thomas McGee, Sylvie Jeannin |
| 2000 | AAAI | TV Content Recommender System. | Srinivas Gutta, Kaushal Kurapati, K. P. Lee, Jacquelyn Martino, John Milanski, J. David Schaffer, John Zimmerman |
| 2000 | FOGA | Niches in NK-Landscapes. | Keith E. Mathias, Larry J. Eshelman, J. David Schaffer |
| 2000 | GECCO | Code Compaction Using Genetic Algorithms. | Keith E. Mathias, Larry J. Eshelman, J. David Schaffer, Lex Augusteijn, Paul F. Hoogendijk, Rik van de Wiel |
| 1998 | FOGA | The Effect of Incest Prevention on Genetic Drift. | J. David Schaffer, Murali Mani, Larry J. Eshelman, Keith E. Mathias |
| 1998 | PPSN | The Effects of Control Parameters and Restarts on Search Stagnation in Evolutionary Programming. | Keith E. Mathias, J. David Schaffer, Larry J. Eshelman, Murali Mani |
| 1996 | FOGA | Convergence Controlled Variation. | Larry J. Eshelman, Keith E. Mathias, J. David Schaffer |
| 1994 | FOGA | Productive Recombination and Propagating and Preserving Schemata. | Larry J. Eshelman, J. David Schaffer |
| 1992 | FOGA | Real-Coded Genetic Algorithms and Interval-Schemata. | Larry J. Eshelman, J. David Schaffer |
| 1990 | FOGA | Spurious Correlations and Premature Convergence in Genetic Algorithms. | J. David Schaffer, Larry J. Eshelman, Daniel Offutt |
| 1989 | ICML | Using Multiple Representations to Improve Inductive Bias: Gray and Binary Coding for Genetic Algorithms. | Rich Caruana, J. David Schaffer, Larry J. Eshelman |
| 1989 | IJCAI | Representation and Hidden Bias II: Eliminating Defining Length Bias in Genetic Search via Shuffle Crossover. | Rich Caruana, Larry J. Eshelman, J. David Schaffer |
| 1988 | ICML | Representation and Hidden Bias: Gray vs. Binary Coding for Genetic Algorithms. | Rich Caruana, J. David Schaffer |
| 1985 | IJCAI | Multi-Objective Learning via Genetic Algorithms. | J. David Schaffer, John J. Grefenstette |