• Ensuring accurate staining with deep generative networks for virtual IHC in pathology.

    A modification to the loss function of a CycleGAN to improve its mapping ability for pathology images by enforcing realistic stain replication while retaining tissue structure.

  • Evolution of Convolutional Neural Networks for Lymphoma Classification.

    We investigated using deep learning and evolutionary algorithms to classify Lymphoma, achieving a 10-fold cross-validation accuracy of 95.64% and a single run accuracy of 98.41%, surpassing average human pathologist performance.

  • It's Good to Chat?: Evaluation and Design Guidelines for Combining Open-Domain Social Conversation with Task-Based Dialogue in Intelligent Buildings.

    A deployed conversational AI system for a public university building demonstrates no significant difference in task completion between open-domain social chat and task-only versions, but users prefer task-only interactions for future use.