FindInfinite Labs is an independent research practice operating at the intersection of quantum information, computational biology, and applied artificial intelligence. We build the systems, train the operators, and advise the institutions defining the next decade of scientific work.
Original work in quantum information theory, error mitigation, and the algorithmic foundations of fault-tolerant computing — pursued through university affiliation and direct industry partnership.
Research Programs →Deployment-grade systems for organizations that need more than demos: production AI infrastructure, evaluation pipelines, and operator-grade training that survives contact with reality.
Consulting →Graduate-level instruction at the University of Oregon and corporate training programs that prepare engineering, research, and product organizations for the AI-native decade.
Training Programs →The next phase of quantum computation will not be defined by qubit count alone, but by the engineering systems that make scaling tractable — error correction, control software, and the algorithmic interfaces that connect quantum coprocessors to classical workloads.
FindInfinite Labs operates an active research program on fault-tolerance overhead, hybrid algorithm design, and the foundational mathematics of quantum advantage. Our work is conducted in the open, under university affiliation, and with direct industry collaborators.
We collaborate with biopharma research groups on the parts of the discovery pipeline that machine learning can demonstrably accelerate: molecular dynamics post-processing, structure-based virtual screening, and the integration of generative models into experimental loops.
Our position is non-speculative: deploy what works, instrument what's promising, and reject the rest.
Closed-form models for logical-qubit overhead under measured noise channels in superconducting and ion-trap architectures.
Hybrid VQE pipelines targeting molecular ground states with ansätze designed for near-term hardware constraints.
Diffusion-based ensemble generation conditioned on MD trajectories to expose druggable conformations missed by static structures.
Transfer-learning architectures evaluated against held-out perturbation libraries; emphasis on calibrated uncertainty rather than benchmark inflation.
Open-source tooling for offline & online evaluation of agent pipelines, with a bias toward measurable regressions and away from vibes-based benchmarks.
Annual seminar at University of Oregon covering the systems, theory, and operational realities of training and serving frontier models.
"The frontier is not a place you visit. It is a discipline you build, one experiment at a time."
FindInfinite Labs takes on a small number of new partnerships each cycle. We work best with organizations that have specific scientific or engineering ambitions, internal technical depth, and a long planning horizon.
