People

Amy Alvarez is pursuing her B.S. in Computer Engineering and Mathematics at the Florida Institute of Technology. She investigates how autonomous systems perceive, decide, and act in safety-critical settings. 

Her work lies at the intersection of perception and verification for real-world autonomy, with applications in aerospace and autonomous navigation. She has developed and contributed to methodologies in computer vision, spanning semantic scene understanding, automated line identification, and Gaussian splatting-based 3D reconstruction, including contributions to the AssistTaxi dataset for runway and taxiway analysis. Her research is supported through the Automated Data Labeling and Assurance for Autonomous Aircraft Vision Systems (ADLAAAVS) project, funded by NASA. In parallel, she has experience in FPGA development and hardware–software integration, focusing on embedded and reconfigurable computing for real-time systems.

Current Research Interests: 

Autonomous Systems, Computer Vision, Formal Verification, Reinforcement Learning, Reconfigurable Computing, Machine Learning

Papers Under Review:

[1] Inspection Orbit Selection for Gaussian Splatting-Based 3D Reconstruction of Unknown RSOs. Under review at Journal of Spacecraft and Rockets, 2026.

[2] Modular Test-Time Input Space Refinement for Few-Shot Segmentation. Under review at IEEE Transactions on Emerging Topics in Computational Intelligence, 2026. 

Published Research Papers:

[1] AssistTaxi-v2: A Scalable Dataset for Taxiway/Runway Scene Understanding Under Diverse Conditions. AIAA SciTech Forum, 2026. https://doi.org/10.2514/6.2026-1774.

[2] Adapt, But Don’t Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift. International Conference on Computer Vision (ICCV), 2025. https://doi.org/10.48550/arXiv.2507.18653

[3] On Optimal Observation Orbits for Learning Gaussian Splatting-based 3D Models of Unknown Resident Space Objects. AIAA SciTech Forum, 2025. https://doi.org/10.2514/6.2025-1780

[4] Runway vs. Taxiway: Challenges in Automated Line Identification and Notation Approaches. IEEE International Systems Conference (SysCon), 2025. https://doi.org/10.48550/arXiv.2501.18494 

Awards and Recognitions:

• Outstanding Student of the Year, Department of Electrical Engineering and Computer Science (2026)

• Outstanding Student of the Year, Department of Electrical Engineering and Computer Science (2025)

• Sigma Xi Honor Society (2025)

• Alpha Alpha Alpha Honor Society (2025)

• Phi Eta Sigma Honor Society (2024)

• Faculty Senate Scholarship (2024)

• Fantastic First Year Student (2024)