QC · 01
Surface-code resource estimation under realistic noise
Closed-form models for logical-qubit overhead under measured noise channels.
STATUSActive
PHASEII / III
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Eleven concurrent programs across quantum information, computational biology, and AI systems engineering. Conducted under university affiliation, in collaboration with industrial partners, and held to the standards of peer-reviewed scientific work.
Closed-form models for logical-qubit overhead under measured noise channels.
Hybrid VQE pipelines targeting molecular ground states on near-term hardware.
Honest accounting of where structured quantum speedup is theoretically and empirically defensible.
Diffusion-based ensemble generation conditioned on MD trajectories.
Transfer-learning architectures with calibrated uncertainty.
Closed-loop integration of generative models with wet-lab experimental design.
Open-source tooling for offline & online evaluation of agent pipelines.
Batching, caching, and orchestration patterns for long-horizon agent runs.
Isolation, capability boundaries, and audit-grade observability for autonomous code execution.
We collaborate with universities, industrial labs, and mission-driven institutions on programs that meet our scientific bar and theirs.