Translational initiatives and foundational studies currently underway at Pellucid Research.
A structured graph pipeline for extracting claims, methods, and outcomes from technical literature across machine learning and biomedical domains.
Sequence learning with causal regularization for robust phenotype prediction under sparse and partially observed biological measurements.
A benchmark platform for measuring reasoning consistency and verifiability of language systems on mathematics-heavy tasks.
Instrumentation stack for tracking uncertainty, calibration, and failure mode evolution during iterative model development.
We evaluate external collaboration requests based on scientific value, data feasibility, and whether the resulting work can be shared as durable public research.