Abstract
The number of published journals, conferences, and research papers in computer science is increasing rapidly, which has led to a challenge in coming up with new and unique ideas for research. To alleviate the issue, this paper uses artificial neural networks (ANNs) to generate new computer science research ideas. It does so by using a dataset collected from IEEE published journals and conferences to train an ANN model. The results reveal that the model has a 14% success rate in generating usable ideas. The outcome of this paper has implications for helping both new and experienced researchers come up with novel research topics.