Projects
Foundations and algorithms for reliable, adaptive AI.
My research connects optimization and structured representations with generative-model alignment, continual adaptation, causal inference, and AI research agents. Explore the projects below or browse the full publication list.
Generative Models & Alignment
Semantic guidance, inverse problems, and efficient adaptation of diffusion and flow models.
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AI Research Agents
Reasoning, experiment selection, and efficient automated machine-learning research.
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Causal Inference & Transportability
Robust causal abstractions and transferring causal conclusions across populations.
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Low-Rank Learning & Optimization
Matrix factorization, implicit regularization, and efficient optimization with guarantees.
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Tensor Decomposition
Structured representations, automatic rank selection, and online learning.
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Continual Learning & Adaptation
Sequential learning, retention of prior knowledge, and efficient model adaptation.
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Robust Probabilistic Inference
Generalised variational inference, federated learning, and uncertainty under misspecification.
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Robust Subspace Recovery
Implicit regularization and recovery of unknown-dimensional subspaces from outliers.
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Adversarial Robustness
Reverse engineering attacks through sparse recovery and generative-model inversion.
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