I lead AI innovation initiatives at Google focused on the federal sector, combining research rigor with real-world deployment. My work spans NLP, computer vision, and generative AI—from parameter-efficient architectures to production systems.
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Parameter-efficient compression model architecture for NLP tasks achieving BERT-level performance at a fraction of the computational requirements |
Computer vision neural network achieving Kaggle 2nd place (RMSE: 1.28637) detecting 15 facial landmarks |
Interested in AI research, federal innovation, or potential collaboration? Explore my full portfolio or reach out.
Always happy to discuss ML architectures, research ideas, or interesting problems.

