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Color Invariant Skin Segmentation

Design guidelines for narrative maps in sensemaking tasks

Narrative Sensemaking: Strategies for Narrative Maps Construction

B. F. K. Norambuena, T. Mitra and C. North, “Narrative Sensemaking: Strategies for Narrative Maps Construction,” 2021 IEEE Visualization Conference (VIS), 2021, pp. 181-185

Semantic Explanation of Interactive Dimensionality Reduction

Y. Bian, C. North, E. Krokos and S. Joseph, “Semantic Explanation of Interactive Dimensionality Reduction,” 2021 IEEE Visualization Conference (VIS), 2021, pp. 26-30

Improving Zero-Shot Event Extraction via Sentence Simplification

Contrastive Graph Convolutional Networks for Hardware Trojan Detection in Third Party IP Cores

EINNs: Epidemiologically-Informed Neural Networks

Twelve Virginia Tech faculty join Innovation Campus

Twelve highly accomplished Virginia Tech faculty experts in computer science and computer engineering have formally affiliated with the Virginia Tech Innovation Campus in Alexandria. This first cohort of Innovation Campus faculty will play a vital role in shaping the new campus by helping to establish key research themes, enhancing the project-based curriculum, and developing the campus governance […]

Sanghani Center Student Spotlight: Mandar Sharma

Would you like a virtual assistant that could go through chunks of large reports with pages upon pages of tables and raw numeric data and summarize it all in a short paragraph?  This is what Mandar Sharma is trying to accomplish with his Ph.D. research in the area of natural language generation. “The progress of artificial intelligence […]

CI Fellow Rebecca Faust brings expertise on human-AI interaction methods for dimension reduction to Sanghani Center work with Chris North

A 2021 Computing Innovation (CI) Fellow, postdoc Rebecca Faust, has been working with Chris North, professor in computer science and associate director at the Sanghani Center for Artificial Intelligence and Data Analytics, since January. They are exploring how to create explanations of the effects of semantic interactions on a deep learning model through the analysis of perturbations and […]