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Bradford, M., Seefried, E., Krishnaswamy, N., & Blanchard, N. (2024). Thematic Analysis of Foreign Language Learning in a Virtual Environment. In 27th Annual CyberPsychology, CyberTherapy & Social Networking Conference. [DOI]
Castillon, I., Chartier, T., Venkatesha, V., Okada, N. S., Davis, A., Cleary, A. M., & Blanchard, N. (2024). Automatically Identifying the Human Sense of Familiarity Using Eye Gaze Features. In International Conference on Human-Computer Interaction (pp. 291–310). Springer. [DOI]
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Nath, A., Jamil, H., Ahmed, S. R., Baker, G., Ghosh, R., Martin, J. H., Blanchard, N., & Krishnaswamy, N. (2024). Multimodal Cross-Document Event Coreference Resolution Using Linear Semantic Transfer and Mixed-Modality Ensembles. In Proceedings of the 2024 Joint International Conference on Computational Linguistics. [DOI]
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Venkatesha, V., Nath, A., Khebour, I., Chelle, A., Bradford, M., Tu, J., & Blanchard, N. (2024). Propositional Extraction from Natural Speech in Small Group Collaborative Tasks. In Proceedings of the 17th International Conference on Educational Data Mining. [DOI]
Seefried, E., Jung, C., Fitzgerald, J., Bradford, M., Chartier, T., & Blanchard, N. (2024). Balancing Quality and Quantity: The Impact of Synthetic Data on Smoke Detection Accuracy in Computer Vision. In Synthetic Data for Computer Vision Workshop@ CVPR 2024. [DOI]
Khebour, I., Brutti, R., Dey, I., Dickler, R., Sikes, K., Lai, K., Bradford, M., Cates, B., & Blanchard, N. (2024). When Text and Speech Are Not Enough: A Multimodal Dataset of Collaboration in a Situated Task. Journal of Open Humanities Data, 10. [DOI]
Jamil, H., Liu, Y., Blanchard, N., Kirby, M., & Peterson, C. (2023). Leveraging Linear Mapping for Model-Agnostic Adversarial Defense. Frontiers in Computer Science, 5, 1274832.[DOI]
Fitzgerald, J., Seefried, E., Yost, J. E., Pallickara, S., & Blanchard, N. (2023). Paying Attention to Wildfire: Using U-Net with Attention Blocks on Multimodal Data for Next Day Prediction. In Proceedings of the 25th International Conference on Multimodal Interaction.[DOI]
Castillon, I., Venkatesha, V., Caglar, T., Liu, X., Cleary, A., and Blanchard, N. (2023). Predicting the Occurrence of Déjà Vu using Eye Features. In Association for Computing Machinery Graduate Student Research Competition, awarded 3rd place. CMD-IT/ACM Richard Tapia Celebration of Diversity in Computing Conference.
VanderHoeven, H., Blanchard, N., and Krishnaswamy, N. (2023). Robust Motion Recognition using Gesture Phase Annotation. In International Conference on Human-Computer Interaction (HCII). Springer.[DOI]
Kandoi, C., Jung, C., Mannan, S., VanderHoeven, H., Meisman, Q., Krishnaswamy, N., and Blanchard, N. (2023). Intentional Microgesture Recognition for Extended Human-Computer Interaction. In International Conference on Human-Computer Interaction (HCII). Springer. [DOI]
Kuvar, V., Blanchard, N., Colby, A., Allen, L., & Mills, C. (2023). Automatically detecting task-unrelated thoughts during conversations using keystroke analysis. User Modeling and User-Adapted Interaction, 33(3), 617-641. [DOI]
Bradford, M., Khebour, I., Blanchard, N., & Krishnaswamy, N. (2023). Automatic detection of collaborative states in small groups using multimodal features. In International Conference on Artificial Intelligence in Education, 767-773. [DOI]
Terpstra, C., Khebour, I., Bradford, M., Wisniewski, B., Krishnaswamy, N., & Blanchard, N. (2023). How good is automatic segmentation as a multimodal discourse annotation aid? In Workshop on Interoperable Semantic Annotation (ISA-19). [DOI]
Pickard, W., Sikes, K., Jamil, H., Chaffee, N., Blanchard, N., Kirby, M., & Peterson, C. (2023). Exploring fMRI RDMs: Enhancing Model Robustness Through Neurobiological Data. Frontiers in Computer Science, 5, 1275026. [DOI]
Jamil, H., Liu, Y., Caglar, T., Cole, C., Blanchard, N., Peterson, C., & Kirby, M. (2023). Hamming similarity and graph Laplacians for class partitioning and adversarial image detection. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). [DOI]
Roy, S., Roygaga, C., Blanchard, N., & Bharati, A. (2023). A computer vision method for estimating velocity from jumps. In Computer Vision 4 Winter Sports (CV4WS) at Winter Conference for AI. [DOI]
Jamil, H., Liu, Y., Cole, C., Blanchard, N., King, E. J., Kirby, M., & Peterson, C. (2022). Dual Graphs of Polyhedral Decompositions for the Detection of Adversarial Attacks. In The 6th Workshop on Graph Techniques for Adversarial Activity Analytics. [DOI]
Krishnaswamy, N., Pickard, W., Cates, B., Blanchard, N., & Pustejovsky, J. (2022). The voxworld platform for multimodal embodied agents. LREC Proceedings, 13. [DOI]
McNeely-White, D., Sattelberg, B., Blanchard, N., & Beveridge, R. (2022). Canonical face embeddings. IEEE Transactions on Biometrics, Behavior, and Identity Science, 4(2), 197-209. [DOI]
Bradford, M., Hansen, P., Lai, K., Brutti, R., Dickler, R., Hirshfield, L. M., Pustejovsky, J., Blanchard, N., and Krishnaswamy, N. (2022). Challenges and Opportunities in Annotating a Multimodal Collaborative Problem Solving Task. In Workshop on Interdisciplinary Approaches to Getting AI Experts and Education Stakeholders Talking (Bridging AIEd). International AIEd Society. [DOI]
Castillon, I., Venkatesha, V., VanderHoeven, H., Bradford, M., Krishnaswamy, N., and Blanchard, N. (2022). Multimodal Features for Group Dynamic-Aware Agents. In Workshop on Interdisciplinary Approaches to Getting AI Experts and Education Stakeholders Talking (Bridging AIEd). International AIEd Society. [DOI]
Bradford, M., Hansen, P., Beveridge, R., Krishnaswamy, N., and Blanchard, N. (2022). A deep dive into microphones for recording collaborative group work. In International Conference on Educational Data Mining (EDM). International Educational Data Mining Society. [DOI]
Roygaga, C., *Patil, D., *Boyle, M., Reiser, R., Bharati, A., Blanchard, N. (2022) APE-V: Athlete Performance Evaluation using Video. In Proceedings 2022 IEEE Winter Conference on Applications of Computer Vision (WACV) Workshops. IEEE. [DOI]
Gorbett, M., Blanchard, N. (2022). Utilizing network properties to detect erroneous inputs. In Proceedings 2022 IEEE Winter Conference on Applications of Computer Vision (WACV) Workshops. IEEE. [DOI]
Danilyuk, E. (2022) PortfoliU Project: Investigating an Open-Source Repository of Personal Portfolio Websites and How they Benefit Computer Science Students. 2022 Rocky Mountain Conference for Women in Computing. Poster + Invited Talk.
Trabelsi, A., Beveridge, R. J., & Blanchard, N. (2021). Motion prediction performance analysis for autonomous driving systems and the effects of tracking noise. arXiv preprint arXiv:2104.08368. [DOI]
Sakimoto, S. E. H., Lewis, D. D., Dileep, S., Memon, P., Beveridge, J. R., & Blanchard, N. (2021). Deep Learning for an Inventory of Small to Midsize Volcanic Edifices on Mars. 52nd Lunar and Planetary Science Conference, 1626. [DOI]
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Trabelsi, A., Chaabane, M., Blanchard, N., & Beveridge, R. (2021). A pose proposal and refinement network for better 6D object pose estimation. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. [DOI]
Dileep, S., Zimmerle, D., Beveridge, R., and Vaughn, T. (2020). Automated Identification of Oil Field Features using CNNs. In NeurIPS 2020 Workshop on Tackling Climate Change with Machine Learning. Neural Information Processing Systems. [DOI]
Chaabane, M., Trabelsi, A., Blanchard, N., & Beveridge, R. (2020). Looking Ahead: Anticipating Pedestrians Crossing with Future Frames Prediction. In 2019 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE. [DOI]
McNeely-White, D., Sattelberg, B., Blanchard, N., & Beveridge, R. (2020). Exploring the interchangeability of CNN embedding spaces. arXiv preprint arXiv:2010.02323. [DOI]