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Deep Learning
Deep Learning
Explainability
Explainability
Model attribution
Integrated measures
Kernel formulations
Papers: ICPR 2024 (1), ICPR 2024 (2), ICML-W 2023, ICML-W 2023
Optimizations in Training
Optimizations in Training
Data reduction
Network optimization
Computer Vision
Computer Vision
Robustness & Adversarial Attacks
Robustness & Adversarial Attacks
Reconstructive training for image classification tasks.
Papers: SADM 2025, WACV-W 2022, ISVC 2019
Other applications in 3D objects: ICIP 2022
Eye Tracking for VR/AR
Eye Tracking for VR/AR
Semantic segmentation of images and video.
Papers: ECCV-W 2020 [video], ICCV-W 2019
Other applications in VR/AR: VR 2023, NLPIR 2024
Applications in the Physical Sciences
Applications in the Physical Sciences
Deep Learning for Nuclear Materials
Deep Learning for Nuclear Materials
Ongoing collaborative work with UTSA Physics, UTSA Engineering, Los Alamos National Lab, Argonne National Lab, UNLV, St. Mary’s.
Deep neural networks for semantic segmentation of micrographs and images of nuclear fuel forms during the fabrication process.
Papers: CVPR-W 2025 [2], IEEE Access 2023
Datasets: Graphite-23 [IEEE Dataport]
Computer Science Education
Computer Science Education
Computer Science for San Antonio
NSF CSForAll - CS4SA-HS: Developing a collaborative of secondary computer science teachers to increase Latinx participation in CS
Papers: SIGCSE 2023 poster, RESPECT 2022, SIGCSE 2024
AI Resources for Introductory CS
AI Resources for Introductory CS
Instructional resources development advocating for the use of LLMs and other AI technologies in CS1 instruction & beyond, with an emphasis on software verification.
Papers: CCSC-NE 2025, SIGCSE 2024
CS-CURE, a course-based undergraduate research experience bridging subfields within computer science.
Papers: SIGCSE 2025, SIGCSE 2024 poster
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