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Undergraduate researcher specialized in computer vision fairness, sparse transformer architectures, and reliable AI safety frameworks.
Real-time synchronized with Google Firebase Firestore.
Xavier Duindam. Investigating re-weighting optimization techniques for radiological vision models across demographic subsets.
Xavier Duindam. Real-time latent embedding monitoring to detect prompt injection vulnerabilities in enterprise LLM APIs.
Custom baseline neural networks, PyTorch training pipelines, hyperparameter tuning, and performance benchmarking.
Exploratory data analysis (EDA), statistical skew verification, fairness re-balancing, and data sanitization pipelines.
Assisting labs and enterprises with prompt vulnerability testing, model red-teaming, and governance compliance reviews.
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