ML Systems Architect | Applied Scientist | Researcher | Co-Founder
Operating on scaling-law asymptotics and post-attentional inductive biases. Designing sparse, retrieval-conditioned, multimodal foundation systems under compute-optimal regimes and beyond canonical attention regimes - and adjacent frontier AI research.
Predicted similarities for 3D tomograms that reduced false positives and improved accuracy to 64% in detecting outliers, using contextual learning, DoG (difference of Gaussian) and multivariate statistical analysis
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Produced script that can automatically find repeating features in cryo-electron tomograms with the use of Machine Learning