| ROLE AI Systems Engineer |
PLATFORMS Azure / GCP |
FOCUS AI Systems / Security |
STATUS Building + Reviewing |
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Adversarial robustness evaluation of pretrained ResNet-34 and DenseNet-121 classifiers using FGSM, PGD, and localized patch attacks. 76.0% → 0.2% ResNet-34 top-1 accuracy under PGD at |
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Standalone engineering example for screening fictional research abstracts against explicit inclusion criteria using structured AI outputs. |
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Standalone Vertex AI example that converts synthetic machine-learning experiment metrics into structured technical analysis. |
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Engineering portfolio documenting selected work across AI systems, ML security, systems performance, and governance. |
LANGUAGES
Python ████████████████████
TypeScript ██████████████
C++ ████████████
AI / ML
PyTorch adversarial evaluation · model analysis
Azure AI systems · structured workflows
Vertex AI structured generation · ML analysis
SYSTEMS
Docker reproducible environments
Git version control · engineering workflow
Astro portfolio systems · web architecture
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The City College of New York NYU Tandon School of Engineering |
CodePath Hackathons |
AI SYSTEMS ◆ ML SECURITY ◆ GOVERNANCE ◆ SYSTEMS PERFORMANCE
Much of my professional engineering work is developed in private environments and is therefore not represented by the public contribution graph.
FZ / END OF DOSSIER