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Students working with the cluster

Publications

Supercomputing Research at UW-Eau Claire

UWEC has maintained its commitment to high-impact learning practices with an emphasis on undergraduate research. Students (highlighted) and their mentor collaborators are continuously exploring newer problems, studying together, and publishing their findings.

To see how supercomputing has continuously pushed forward research, check out all of the following publications since 2012 that have used our campus resources:

2024

  • High-performance computing in undergraduate education at primarily undergraduate institutions in Wisconsin: Progress, challenges, and opportunities

    Hebert, J., Hratisch, R., Gomes, R., Kunkel, W., Marshall, D., Ghosh, A., Doss, I., Ma, Y., Stedman, D., Stinson, B., Varghese, A., Mohr, M., Rozario, P., & Bhattacharyya, S. (2024). High-performance computing in undergraduate education at primarily undergraduate institutions in Wisconsin: Progress, challenges, and opportunities. In Education and Information Technologies. Springer Science and Business Media LLC. https://doi.org/10.1007/s10639-024-12582-6 

  • Optimizing Mobile Vision Transformers for Land Cover Classification

    Rozario, P. F., Gadgil, R., Lee, J., Gomes, R., Keller, P., Liu, Y., Sipos, G., McDonnell, G., Impola, W., & Rudolph, J. (2024). Optimizing Mobile Vision Transformers for Land Cover Classification. In Applied Sciences (Vol. 14, Issue 13, p. 5920). MDPI AG. https://doi.org/10.3390/app14135920 

2023

  • Analysis of Swin-UNet vision transformer for Inferior Vena Cava filter segmentation from CT scans

    Gomes, R., Pham, T., He, N., Kamrowski, C., & Wildenberg, J. (2023). Analysis of Swin-UNet vision transformer for Inferior Vena Cava filter segmentation from CT scans. In Artificial Intelligence in the Life Sciences (Vol. 4, p. 100084). Elsevier BV. https://doi.org/10.1016/j.ailsci.2023.100084

  • Deep Learning Patch-Based Approach for Hyperspectral Image Classification

    Rozario, P. F., Ruehmann, E., Pham, T., Sun, T., Jensen, J., Jia, H., Yu, Z., & Gomes, R. (2023). Deep Learning Patch-Based Approach for Hyperspectral Image Classification. 2023 IEEE International Conference on Electro Information Technology (eIT). IEEE. https://doi.org/10.1109/eit57321.2023.10187387 

  • Inter-institutional Resource Sharing in Undergraduate HPC Education: Interviews with University Administrators

    Ghosh, A., Kunkel, W., Varghese, A., Ma, Y., Gomes, R., Bhattacharyya, S., Mohr, M., Doss, I., & Hebert, J. (2023). Inter-institutional Resource Sharing in Undergraduate HPC Education. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 (pp. 848–853). SIGCSE 2023: The 54th ACM Technical Symposium on Computer Science Education. ACM. https://doi.org/10.1145/3545945.3569784 

2022

  • A Robust Framework for Deep Learning Approaches to Facial Emotion Recognition and Evaluation

    Siddiqui, N., Reither, T., Black, D., Bauer, T., Hanson, M., & Dave, R., (2022). A Robust Framework for Deep Learning Approaches to Facial Emotion Recognition and Evaluation. 2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML). IEEE. https://doi.org/10.1109/cacml55074.2022.00020 

  • Abstract No. 144 Automated IVC filter detection from abdominopelvic CT exams using deep learning

    Wildenberg, J., Kamrowski, C., Senor, C., Mohan, P., & Gomes, R. (2022). Abstract No. 144 Automated IVC filter detection from abdominopelvic CT exams using deep learning. Journal of Vascular and Interventional Radiology (Vol. 33, Issue 6, p. S67). https://doi.org/10.1016/j.jvir.2022.03.225 

  • Application of Deep Learning to IVC Filter Detection from CT Scans

    Gomes, R., Kamrowski, C., Mohan, P. D., Senor, C., Langlois, J., & Wildenberg, J. (2022). Application of Deep Learning to IVC Filter Detection from CT Scans. Diagnostics, 12(10), 2475. https://doi.org/10.3390/diagnostics12102475

  • Application of Feature Selection and Deep Learning for Cancer Prediction Using DNA Methylation Markers

    Gomes, R., Paul, N., He, N., Huber, A. F., & Jansen, R. J. (2022). Application of Feature Selection and Deep Learning for Cancer Prediction Using DNA Methylation Markers. Genes, 13(9). https://doi.org/10.3390/genes13091557

2021

  • A scalable deep learning framework for breast cancer prediction using DNA methylation data

    Gomes, R.; He, N.; Huber, A.; Jansen, R.; and Paul, N. A scalable deep learning framework for breast cancer prediction using DNA methylation data. American Society of Human Genetics 2021, 2021, (View Poster).

  • Named Entity Recognition in Unstructured Medical Text Documents

    Pearson, C.; Seliya, N.; and Dave, R. Named Entity Recognition in Unstructured Medical Text Documents. 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET), 1–6, 2021 (DOI: https://doi.org/10.1109/ICECET52533.2021.9698694)