MegaScience: Pushing the Frontiers of Post-Training Datasets for Science Reasoning

Reproducible and flexible LLM evaluations for scientific reasoning.

Foundational doctrine establishing the principles behind the Neurotransparency governance framework.

ReCrit: Transition-Aware Reinforcement Learning for Scientific Critic Reasoning

Code and lightweight audit artifacts for auditable repair of scientific reasoning graph extraction on a 350-row benchmark.

BioReasoner: Training LLMs for grounded scientific reasoning. 0% hallucination rate on citations, 100% format adherence. Cross-domain polymathic insights via Scientific Tribunal evaluation.

Framework for building and evaluating explanatory accounts of evidence using Bayesian network inference. Includes interactive Shiny app.

LLM + PDDLStream pipeline for executable science problem solving on SciBench.

Evidence-grounded Sci-Evo scientific evolution dataset built from MinerU-parsed open-access protein-engineering papers.

Scientific computing portfolio covering computational chemistry, biomedical modeling, literature mining, kinetic modeling, biomarker simulation, and AI-assisted scientific evaluation.

GitHub profile README | Ph.D. scientist in aging biology, scientific reasoning, and frontier AI evaluation

Learned influence-topology control for robust multi-agent LLM networks.

Generic Co-Scientist + Experiment-as-Code framework for reusable AI-driven labs

Scientific synthesis engine for literature-to-research-action workflows

Self-reorganizing knowledge structures via truth pressure. Formalizes scientific paradigm shifts computationally — old knowledge is contextualized, not deleted. Three provable invariants. Validated on miasma→germ theory and classical→quantum physics.

Personal website and online resume | Aging biology, bioinformatics, and AI model evaluation

Benchmark for whether LLMs flatten contested scientific mechanisms into false consensus

Benchmark for multimodal contradiction and evidence reconciliation in biological research